Ai Engineering Jobs

Summary: Seeking a ML engineer to optimize pricing models and infrastructure. Requires Python, AWS, and expertise in machine learning.

Skills: python, scikit-learn, xgboost, aws, sql

Summary: Join a high-growth company as a Backend/ML Engineer using Python, LLMs, and Data Extraction to enhance our ML engine and automate workflows.

Skills: python, llms, data extraction, next.js

Summary: Lead ML/AI strategy, developing RL agents for financial services. Requires expertise in machine learning, AWS, and Ruby.

Skills: ruby, aws, python

Summary: Proven software engineering experience in SaaS with strong knowledge in Python is required. Familiarity with modern LLM applications and cloud-based ML workflows is also essential.

Skills: python, saas, llms, rag, cloud-based ml, azure ml, pinecone, langchain, fastapi, document processing, prototyping, software engineering, ai techniques, experimentation, scalability, performance

Summary: A Bachelor's Degree or higher in a related technical field and at least 6 years of professional software development experience are required. Proven expertise in Python and cloud deployments is essent

Skills: python, ai, ml, cloud infrastructure, aws, gcp, terraform, ci/cd, agile, data pipelines, object-oriented design, machine learning models, communication, collaboration, data-driven solutions

Summary: Candidates should have 7+ years of hands-on experience in ML engineering and production model deployment, with expert proficiency in Python and ML frameworks. A deep understanding of transformer archi

Skills: python, ml frameworks, pytorch, tensorflow, jax, transformer architectures, attention mechanisms, nlp, mlops, cloud ml platforms, aws sagemaker, gcp vertex ai, azure ml, docker, kubernetes, llm fine-tuning, multimodal ai models

Summary: Candidates should have 5+ years of experience building and deploying ML systems in production environments, with expertise in Python and frameworks like PyTorch or TensorFlow. A strong background in t

Skills: machine learning, python, pytorch, tensorflow, nlp, computer vision, generative ai, mlops, cloud ml platforms, system design, collaboration, model validation, reproducibility, monitoring, bias checks

Summary: Seeking a Senior AI Engineer to build LLM systems for user interaction. Requires expertise in AI, prompt engineering, and software engineering principles. Key tech: LLMs, APIs, databases.

Skills: llms, api, databases

Summary: Candidates should have 5+ years of progressive AI/ML engineering experience and a proven track record of delivering scalable AI/ML solutions. A Bachelor’s or Master’s degree in a related technical fie

Skills: ai development, machine learning, collaboration, generative ai, mlops, biomedical ai, data privacy, cloud platforms, leadership, communication, innovation, ethical standards, context engineering, prompt engineering, knowledge graphs, agentic ai

Summary: Candidates should have a Bachelor’s or Master’s degree in Computer Science or a related field with over 8 years of frontend development experience. Expertise in modern JavaScript frameworks and strong

Skills: frontend development, react, angular, vue.js, typescript, javascript, html5, css3, sass, less, redux, git, ci/cd, docker, kubernetes, aws, gcp

Summary: Bachelor’s degree in Computer Science or equivalent practical experience is required along with 5+ years of backend development experience, ideally with Python. Familiarity with Python frameworks and

Skills: python, restful apis, fastapi, django, flask, relational databases, postgresql, mysql, orm, git, ci/cd, automated testing, ai, agentic frameworks, asynchronous processing, code reviews, knowledge sharing

Summary: Bachelor's degree in computer science or related field with 1+ years of experience in computer vision algorithms and 4+ years in software/data engineering. Expertise in Python, C++, GoLang, and famili

Skills: computer vision, data engineering, software engineering, robotics, python, c++, golang, sql, opencv, linux, aws, networking, image processing, ai, machine learning, etl

Summary: Candidates should have over 4 years of fullstack software engineering experience and a passion for engineering and learning. Familiarity with modern web development practices and technologies such as

Skills: fullstack software engineering, ai fluency, web application development, python, fast api, typescript, node.js, supabase, aws

Summary: Candidates should have a deep understanding of software engineering with AI/ML or agentic system development. Experience with AWS, Node.js, PostgreSQL, and production-grade AI systems is essential.

Skills: ai engineering, distributed systems, aws, node.js, typescript, postgresql, clickhouse, llm orchestration, performance monitoring, data privacy, security, startup experience, mentoring, observability, real-time analytics, data pipelines

Summary: Candidates should have 3+ years of experience in building production software and possess a strong algorithms background. An empirical research mindset and interest in user-centered product developmen

Skills: applied ai, software engineering, python, c++, typescript, algorithms, empirical research, experiment design, data visualization, product development, user feedback, robust systems, api development, machine learning, collaboration, desktop applications

Summary: A bachelor's degree in a quantitatively rigorous discipline is preferred, along with 1-3 years of relevant experience in data science or consulting. Candidates should have a high level of comfort with

Skills: data science, machine learning, sql, python, problem solving, communication, analytical skills, a/b testing, data analysis, customer insights, operational efficiency, user acquisition, partnership growth, statistical analysis, technical skills, soft skills

Summary: A bachelor's degree in a quantitatively rigorous discipline is preferred, along with 1-3 years of relevant experience in data science or management consulting. Candidates should be comfortable with SQ

Skills: data science, machine learning, sql, python, data analysis, a/b testing, problem solving, communication, customer insights, operational efficiency, statistical analysis, business strategy, user acquisition, partnership growth, automation, technical skills

Summary: A bachelor's degree in a quantitatively rigorous discipline is preferred, along with 1-3 years of relevant experience in data science or consulting. Candidates should be comfortable with SQL or Python

Skills: data science, machine learning, sql, python, problem solving, communication, analytical skills, a/b testing, data analysis, customer insights, operational efficiency, user acquisition, partnership growth, statistical analysis, technical skills, soft skills

Summary: 5+ years of software engineering experience with 2+ years focused on AI systems is required. Deep expertise in LLM implementation and a strong track record of building production AI systems at scale a

Skills: ai systems, llm implementation, software engineering, document analysis, technical leadership, typescript, ai development, problem solving, ownership, continuous learning, startup environment, multi-agent ai systems, legal text processing, rag systems, ai frameworks, prototyping

Summary: 5+ years of software engineering experience, with 2+ years focused on AI systems is required. Deep expertise in LLM implementation and optimization, along with a strong foundation in TypeScript and mo

Skills: ai systems, llm implementation, software engineering, document analysis, technical leadership, typescript, ai development, problem solving, ownership, continuous learning, startup environment, multi-agent ai systems, legal text processing, rag systems, ai frameworks, prototyping

Summary: Candidates must have a Bachelor’s degree with 5+ years of experience, a Master’s degree with 3+ years of experience, or a PhD in a quantitative field. Proficiency in Python and experience with Generat

Skills: artificial intelligence, machine learning, python, data analysis, generative ai, software development, fairness evaluations, ethical standards, compliance, cross-functional collaboration, communication skills, risk mitigation, transparency, accountability, healthcare, responsible ai

Summary: Candidates should have a Master's degree or higher in a quantitative field and at least 3 years of experience managing data scientists. A strong understanding of data science fundamentals and experien

Skills: data science, machine learning, statistical analysis, data preparation, root cause investigation, sql, pandas, r, airflow, bash, linux/unix, git, data governance, analytical frameworks, mentoring, collaboration

Summary: 8-10 years of professional software engineering experience, including technical leadership across squads or groups. Strong hands-on coding skills and familiarity with modern AI/ML tools and APIs.

Skills: ai engineering practices, devops, ci/cd, cloud infrastructure, node.js, kotlin, react, typescript, next.js, react native, ai/ml tools, code quality, system design, collaboration, mentorship, operational excellence

Summary: Candidates should have a Master's degree with 6+ years of experience or a Ph.D. with 3+ years in Data Science or related fields. Strong proficiency in Python, SQL, and ML libraries, along with experie

Skills: machine learning, ai, data science, python, sql, statistical analysis, time series forecasting, regression modeling, classification techniques, cloud platforms, data pipelines, model deployment, business acumen, communication, problem solving, collaboration

Summary: Candidates should have a strong background in data science and experience in developing predictive models. A focus on customer experience and business outcomes is essential.

Skills: data science, customer experience, revenue growth, churn reduction, ltv forecasting, dollars-at-risk scoring, collaboration, communication, accountability, problem solving, curiosity, model development, performance analysis, statistical analysis, machine learning, data analysis

Summary: Candidates must have a Bachelor’s degree in a relevant field and at least 5 years of professional experience in software engineering, ideally in a full stack role. Strong backend development experienc

Skills: 3d computer vision, robotics, software engineering, backend development, 3d reconstruction, point clouds, meshes, visualization, react, three.js, webgl, lidar, 3d mapping, robotics perception, nvidia omniverse, unity, ar/vr systems

Summary: Candidates must have a minimum of a Bachelor's degree in a relevant field and at least 3 years of programming experience in Python. Familiarity with prompt engineering, context engineering, and natura

Skills: python, prompt engineering, context engineering, model context protocol, agent2agent protocol, natural language processing, machine learning, data science, software engineering, ai solutions, generative ai, automation tools, information retrieval, ai performance optimization, cross-functional collaboration, agentic ai systems

Summary: The role requires 8+ years in software, data, or platform engineering, with 5+ years of Python experience. Candidates should have experience with public cloud services and deploying AI-powered product

Skills: software engineering, data engineering, platform engineering, python, public cloud, ci/cd pipelines, ai-powered products, data pipelines, communication, typescript, healthcare experience, event-driven architectures, team growth

Summary: Candidates must have an active DoD Secret clearance and a Bachelor's degree in a relevant field. They should also have over 8 years of experience in data engineering and familiarity with cloud data te

Skills: data mining, statistical analysis, hypothesis testing, segmentation, modeling, predictive models, data technologies, google cloud, aws, microsoft azure, ms products, data engineering, data science, big data, data visualization, client communication

Summary: An advanced degree in a related field and 7+ years of experience in data science or machine learning are required. Candidates should have a deep understanding of machine learning algorithms and experi

Skills: data science, machine learning, ai, python, data visualization, statistical methods, model deployment, cloud data warehouses, mlops, kubernetes, tensorflow, pytorch, continuous improvement, mentoring, collaboration, communication

Summary: Candidates should have a bachelor's degree in a relevant field and extensive experience in applied machine learning, with at least 2 years in a leadership role. Strong coding skills in Python and expe

Skills: computer vision, machine learning, 3d deep learning, team management, python, mlops, data management, model evaluation, generative ai, cross-functional collaboration, mentorship, research, product development, 3d data processing, deep learning frameworks, innovation

Summary: Candidates should have a BS/MS in a relevant field and 8+ years of software development experience, with at least 4+ years focused on AI/ML. Preferred qualifications include experience with RAG archit

Skills: ai/ml system design, retrieval-augmented generation, ai agents, prompt engineering, machine learning models, python, tensorflow, pytorch, mlops, database technologies, cloud platforms, real-time ml pipelines, collaborative development, open-source contributions, responsible ai practices, custom llm solutions

Summary: Candidates should have a Bachelor’s or Master’s degree in a quantitative field and 4 to 5+ years of related experience in data science. Advanced skills in Python, SQL, and ML model evaluation are esse

Skills: data science, machine learning, python, pandas, scikit-learn, pyspark, sql, nlp, mlops, prompt engineering, agentic ai, model deployment, recommendation systems, bias testing, cross-functional collaboration, agile project management

Summary: 5–7 years of experience in data science, applied machine learning, or advanced analytics is required. Strong skills in Python and SQL, with experience in developing forecasting, classification, or sco

Skills: data science, machine learning, python, sql, predictive modeling, data engineering, analytics, forecasting, classification, scoring models, communication skills, modern data workflows, snowflake, dbt, hex, streamlit

Summary: Candidates should possess 7+ years of experience in data science, machine learning, or related roles, with 4+ years of professional experience in Python and major AI/ML frameworks. A Bachelor's or Mas

Skills: data science, machine learning, ai engineering, python, large language models, generative ai, cloud-native ai services, nlp, computer vision, model development, data analysis, feature engineering, model training, testing, deployment, collaboration

Summary: A bachelor's degree in a relevant field is required, along with a basic understanding of statistical analysis and machine learning techniques. Familiarity with programming languages such as Python or

Skills: data analysis, machine learning, data visualization, python, r, sql, statistical analysis, problem-solving, communication, collaboration, creativity, attention to detail

Summary: Candidates should possess 4+ years of experience in cloud-based data engineering for Data Engineer and 7+ years for Senior Data Engineer, with strong skills in SQL, Python, and optionally Scala. A Bac

Skills: data engineering, ai, ml, cloud-based solutions, sql, python, scala, etl processes, data warehousing, big data architecture, agile frameworks, data modeling, infrastructure-as-code, data integrity, problem-solving, communication

Summary: A bachelor's degree in a related field and 4 years of experience in machine learning or AI engineering are required. Proven experience in deploying production-grade AI chatbots and expertise in Python

Skills: python programming, machine learning, nlp, generative ai, chatbot development, conversational ai, large language models, vector databases, prompt engineering, model tuning, sql, data pipelines, ai analytics, voice ai, collaboration, communication

Summary: Bachelor's degree or higher in Computer science, Linguistics, or a related field is required. Solid coding proficiency in Python and professional experience in prompt design are essential.

Skills: python, dataset curation, prompt design, linguistics, natural language processing, machine learning, search patterns, problem-solving, attention to detail, collaboration, communication

Summary: Bachelor's degree or higher in Computer science, Linguistics, or a related field is required. Solid coding proficiency in Python and professional experience in prompt design are essential.

Skills: python, dataset curation, prompt design, linguistics, natural language processing, machine learning, search patterns, problem-solving, attention to detail, collaboration, communication

Summary: Candidates should have 7+ years of experience in Data Science/Analytics and strong proficiency in data manipulation and visualization tools. A bachelor's or advanced degree in a quantitative disciplin

Skills: data science, analytics, stakeholder management, communication, problem solving, data manipulation, sql, python, data visualization, tableau, a/b testing, causal inference, machine learning, quantitative analysis, experimentation, leadership

Summary: Candidates should have 6+ years of experience in data science or machine learning, with expertise in time-series data and deep learning frameworks. Proficiency in Python and SQL, along with a strong u

Skills: data science, machine learning, python, sql, deep learning, aws, signal processing, causal inference, experimental design, time-series data, algorithm development, mentoring, data wrangling, model deployment, embedded systems, biomechanics

Summary: Candidates should have 6+ years of experience in data science or machine learning, with expertise in time-series data and deep learning frameworks. Proficiency in Python and SQL, along with a strong u

Skills: data science, machine learning, python, sql, deep learning, aws, time-series data, signal processing, causal inference, algorithm development, mentoring, data wrangling, experimental design, mlops, embedded systems, biomechanics

Summary: Candidates should have 6+ years of experience in data science or machine learning, with expertise in time-series data and proficiency in Python and SQL. Familiarity with deep learning frameworks and c

Skills: data science, machine learning, python, sql, deep learning, aws, time-series data, signal processing, causal inference, experimental design, mentoring, algorithm development, mlops, wearable technology, biometrics, kinesiology

Summary: Bachelor's or Master's degree in a related field is required, with 5+ years of industry experience in AI and Machine Learning. Experience with LLMs, Generative AI, and advanced techniques is preferred

Skills: ai engineering, machine learning, deep learning, generative ai, prompt engineering, conversational ai, data analysis, python, sql, healthcare experience, voice ai, language models, predictive ai, behavior change, cross-functional collaboration, metabolic health

Summary: Advanced programming expertise in Python and SQL is required, along with deep experience in deploying machine learning models in production. A strong foundation in experimentation frameworks and ML Op

Skills: python, sql, machine learning, deep learning, model evaluation, ml ops, system design, collaboration, mentorship, technical leadership, experimentation, model optimization, ai systems, data science, engineering craftsmanship, feedback loops

Summary: Candidates should have strong experience in product analytics or a similar data-focused role, with expertise in translating complex data into actionable insights. A degree in a related analytical fiel

Skills: product analytics, data analysis, sql, a/b testing, machine learning, statistical analysis, r, python, sas, cohort analysis, time series analysis, funnel analysis, data-driven decision making, communication skills, exploratory analysis, product strategy

Summary: Candidates should have 8+ years in software engineering or data science, with 3+ years in Gen AI or LLM-based systems. Strong programming skills and experience with cloud platforms are essential.

Skills: software engineering, data science, gen ai, llm-based systems, typescript, python, rest api development, containerization, cloud platforms, ai governance, model safety, prompt engineering, team leadership, collaboration, problem-solving

Summary: Candidates should have a degree in a quantitative field and over 5 years of experience in data science or analytics. A strong understanding of machine learning methods and experience with large datase

Skills: data analysis, machine learning, python, pyspark, sql, aws, azure, databricks, data storytelling, communication, identity verification, fraud prevention, dashboarding, interactive presentations, thought leadership, model building

Summary: A Master's degree in a quantitative discipline with two years of experience, or a Bachelor's degree with five years of experience is required. Special skills in various programming languages and data

Skills: python, sql, spark, scikit-learn, causal inference, natural language processing, tensorflow, pytorch, a/b test, data visualization

Summary: An advanced degree in a quantitative field is required along with 3+ years of experience building ML/NLP models. Proficiency in Python and hands-on experience with LLMs and frameworks like PyTorch or

Skills: data science, ai innovation, nlp, llm, python, pytorch, tensorflow, langchain, rag, fine-tuning, aws, machine learning, bias detection, ml pipelines, transformers, self-attention

Summary: Candidates must have 3+ years of hands-on experience in machine learning and a bachelor's degree or higher in a related field. They should possess excellent knowledge of advanced methods, experience w

Skills: machine learning, artificial intelligence, statistical data analytics, data analysis, large language models, software development, rapid prototyping, gcp, aws, health care data analytics, r, python, data mining algorithms, mathematical modeling, communication skills, problem solving

Summary: Candidates should have 10+ years of professional experience in data science or analytics, with at least 3 years in a leadership role focused on marketing analytics. Deep expertise in marketing attribu

Skills: data science, analytics, marketing attribution, customer lifetime value, cohort analysis, marketing performance optimization, python, sql, r, bayesian hierarchical modeling, ridge regression, statistical modeling, leadership, mentoring, communication, business acumen

Summary: Candidates should have 10+ years of experience in data science or analytics, with at least 3 years in a leadership role. Deep expertise in experimental design and a proven track record of building exp

Skills: data science, analytics, python, sql, statistical modeling, a/b testing, causal inference, user behavior modeling, funnel analysis, cohort analysis, product engagement metrics, mentoring, experiment design, statistical rigor, communication skills, experimentation techniques

Summary: Candidates should have a strong understanding of statistical concepts and experience in exploratory analysis. A proven track record of owning complex data projects and proficiency in SQL and Python is

Skills: data storytelling, statistical analysis, machine learning, sql, python, data visualization, causal inference, exploratory analysis, mentorship, ai tools, big data, cloud environment, predictive analytics, experimental design, optimization, data engineering

Summary: Candidates must have a Bachelor's degree in Engineering or a related field, with 5+ years of experience or a Master's degree with 3 years of experience. U.S. citizenship is required due to the nature

Skills: deep learning, mlops, machine learning, data wrangling, statistical methods, python, linux, git, docker, kubernetes, postgresql, mysql, data preparation, experimental design, communication skills, model optimization

Summary: A Bachelor's degree in a relevant field with 2+ years of experience or a Master's degree with 0-1 years of experience is required. Candidates should have experience with Python programming and a worki

Skills: python, sql, machine learning, data visualization, statistical analysis, data preprocessing, problem solving, communication, attention to detail, data quality, aws, scikit-learn, pandas, numpy, tensorflow, matplotlib

Summary: 10+ years of experience in data science and predictive analytics is required. Expertise in Python, R, SQL, and hands-on experience with Snowflake and Tableau is essential.

Skills: data science, predictive analytics, ai, python, r, sql, snowflake, data lake, tableau, business processes, revenue forecasting, customer success, data governance, machine learning, data visualization, communication skills

Summary: The ideal candidate should have 5+ years of full-time data experience, with a strong background in data engineering or analytics engineering. They must also possess expertise in modern data stack tech

Skills: data engineering, analytics engineering, data governance, data management, data infrastructure, etl, elt, python, sql, cloud data platforms, nosql databases, data modeling, machine learning pipelines, documentation, data quality assurance, performance optimization

Summary: Candidates should have a Ph.D. or Master's in a relevant field and at least 2 years of experience managing teams focused on computer vision and deep learning. Proficiency in deep learning frameworks a

Skills: deep learning, computer vision, team leadership, object detection, tracking, semantic segmentation, classification, data analysis, automation, data visualization, python programming, software design, machine learning, automated data annotation, deep learning frameworks, computer vision libraries

Summary: The position requires 3+ years of experience with large language models and strong skills in Python. A creative mindset and a passion for transforming education through AI are essential.

Skills: large language models, python, llmops, ai-driven tutoring, chatbots, content-generation systems, data structures, algorithms, software engineering, creative mindset, mission-driven

Summary: Candidates should be currently enrolled in a relevant degree program and possess strong analytical skills along with foundational knowledge of Python and SQL. An interest in blockchain and experience

Skills: data analysis, python, sql, data manipulation, machine learning, generative ai, communication, problem-solving

Summary: A bachelor's degree in a related field and 6+ years of experience in machine learning, NLP, and AI engineering are required. Proven hands-on experience in deploying production-grade AI chatbots in the

Skills: python programming, machine learning, nlp, ai engineering, data engineering, large language models, generative ai, chatbot development, prompt engineering, model tuning, api orchestration, sql, vector databases, conversational ai, document processing, ai-driven analytics

Summary: Candidates must have a bachelor's degree in a related field, with advanced degrees preferred, and significant experience in AI/ML. Preferred qualifications include experience in deploying machine lear

Skills: ai/ml platform strategy, technical architecture, collaboration, machine learning solutions, python programming, model productionization, cicd automation, nlp/nlg, generative ai, cloud platforms, technical communication, mentorship, architecture practices, data science collaboration, stakeholder communication, algorithm selection, model hyperparameter tuning

Summary: Candidates must have a bachelor's degree in a related field, with advanced degrees preferred. A minimum of 10 years of experience is required, or a master's degree with 7+ years, or a Ph.D. with 2+ ye

Skills: ai/ml platform strategy, technical architecture, collaboration, machine learning solutions, python programming, model productionization, cicd automation, nlp/nlg, generative ai, cloud platforms, technical communication, mentorship, architecture practices, data science collaboration, stakeholder engagement, algorithm selection, model hyperparameter tuning

Summary: Candidates should have a bachelor's or master's degree in a relevant field and at least 7 years of experience in AI/ML model deployment. Strong skills in Python, cloud platforms, and natural language

Skills: data science, ai applications, machine learning, natural language processing, generative ai, cloud platforms, python, statistical principles, aiops, model deployment, vector databases, knowledge graphs, agile methodologies, problem solving, performance tuning, architecture design

Summary: A bachelor's degree in a relevant field and proven experience in the insurance industry are required. Strong analytical skills and proficiency in programming languages for data analysis are essential.

Skills: data analysis, predictive modeling, statistical modeling, machine learning, python, r, sas, sql, insurance regulations, project management, communication skills, analytical skills, business acumen, mentoring, decision making

Summary: Candidates should have proven experience in architecting and shipping end-to-end AI-powered solutions, with strong knowledge of generative AI and LLMs. Hands-on experience with AI platforms and the ab

Skills: ai solutions, generative ai, llms, rag pipelines, vector databases, agentic workflows, apis, model lifecycle management, prompt engineering, deployment, collaboration, problem-solving, communication, leadership

Summary: Bachelor’s degree in a related field and 4+ years of industry experience as a Data Scientist or similar role are required. Proven track record in designing and deploying recommendation engines and str

Skills: data science, machine learning, recommendation engines, python, data engineering, collaboration, technical leadership, data visualization, automation tools, personalization, stakeholder engagement, project management, advanced analytics, user engagement, business problem solving, innovation

Summary: Candidates should have a PhD or Master's degree in a related field with relevant work experience. Experience with machine learning model deployment and programming in Python is essential.

Skills: machine learning, signal processing, data analysis, python, c/c++, time-series analysis, data collection, statistical evaluation, cross-functional collaboration, exploratory research, algorithm development, data cleaning, model building, model tuning, communication skills, problem solving

Summary: Experience with LLM evaluation and the development lifecycle of LLM features is required. Candidates should be comfortable working with Python and building APIs using frameworks such as FastAPI or Dja

Skills: ai engineering, machine learning, llm applications, python, api development, fastapi, django, google cloud, kubernetes, docker

Summary: Candidates should have an owner/builder mindset with at least 4 years of experience in backend/platform systems. They must be comfortable with ambiguity and have experience in data integration and clo

Skills: python, cloud infrastructure, data integration, backend systems, agent orchestration, graph databases, observability, reliability, multi-tenant systems, product development, agile methodologies, data privacy, event-driven architecture, fastapi, graphql, kubernetes

Summary: Candidates must have a minimum of 7+ years of experience in a P&C/General/Health insurance pricing role and possess FCAS credentials. A strong understanding of data science and machine learning techni

Skills: actuarial science, data science, machine learning, predictive modeling, communication skills, problem solving, creativity, risk analysis, glms, gams

Summary: Candidates should have a bachelor's degree in a related field and proven insurance business knowledge. Strong technical aptitude in programming languages such as Python, R, SAS, or SQL is required.

Skills: analytics, decision sciences, predictive analytics, predictive modeling, r programming

Summary: Requires a High School Diploma or equivalent and the student must be pursuing a Bachelor’s or advanced degree in an applicable discipline. Familiarity with AI concepts and strong communication skills

Skills: python, machine learning, generative ai, natural language processing, computer vision, simulation, xr/vr, data science, model development, experimentation, applied machine learning, mlops, devops, cloud platforms, communication skills, problem solving

Summary: Candidates must have 2-3 years of experience in AI/ML and enterprise software, with a comprehensive command of machine-learning algorithms. Proficiency in Python and Java, along with experience in clo

Skills: machine learning, generative ai, mlops, python, java, docker, kubernetes, aws, azure, gcp, data analysis, feature engineering, devops, security, compliance, stakeholder management

Summary: Candidates must have 3-5 years of experience in AI/ML and enterprise software, with a comprehensive command of machine-learning algorithms. A Master's degree with 8+ years or a Bachelor's degree with

Skills: machine learning, generative ai, mlops, python, java, docker, kubernetes, aws, azure, gcp, data analysis, feature engineering, devops, security, compliance, stakeholder management

Summary: Candidates should have 3-5 years of experience in AI/ML and enterprise software, with a strong command of machine-learning algorithms. A Master's degree with 8+ years or a Bachelor's degree with 10+ y

Skills: machine learning, generative ai, mlops, python, java, docker, kubernetes, aws, azure, gcp, data analysis, feature engineering, devops, security, compliance, stakeholder management

Summary: Candidates should have 5+ years of hands-on experience in data science and AI/ML product development, with expertise in cloud-based ML platforms and proficiency in Python and SQL. Familiarity with MLO

Skills: data science, machine learning, ai solutions, cloud-based ml platforms, python, sql, docker, kubernetes, data pipelines, feature engineering, model deployment, mlops, statistical analysis, communication skills, agile, nlp

Summary: A minimum of 30 completed college-level credit hours in Data Science or a related field is required by the start date. Interns should have hands-on development experience and the ability to translate

Skills: data science, software development, agile, node.js, javascript, java, c#, sql, html, css, git, restful web services, object-oriented design, database diagramming, systems diagramming, technical documentation

Summary: Candidates should have advanced knowledge of modern OOP languages and deep understanding of Dynamics 365 and related services. A minimum of 4 years of professional experience in software development a

Skills: artificial intelligence, microsoft dynamics365, microsoft power platform, full stack development, api management, azure services, docker, kubernetes, data structures, algorithms, open-source frameworks, service integrations, agile scrum, complex system design, automation, workflows