Ai Engineering Jobs

Summary: A minimum of 4 years of hands-on experience in AI/ML development is required, along with proficiency in Python and modern ML libraries. Familiarity with cloud platforms and experience with MLOps pipelines are also preferred.

Skills: ai engineering, machine learning, python, api development, data pipelines, observability, collaboration, cloud platforms, mlops, generative ai, prompt engineering, fastapi, flask, containerization, vector databases, agent frameworks

Summary: Candidates should have 8+ years of experience in Python and 3+ years in deploying high-volume AI/ML systems. Deep expertise in AI inference services and a strong understanding of the conversational AI lifecycle is essential.

Skills: python, conversational ai, machine learning, deep learning, natural language processing, reinforcement learning, azure, aws, microservices, asynchronous messaging, git, unit testing, debugging, profiling, cloud architecture, data storage

Summary: Candidates should have 10-15+ years in software engineering with significant leadership experience in AI/ML systems. A proven history of shipping LLM-powered features and expertise in backend systems and cloud infrastructure is essential.

Skills: ai systems strategy, machine learning, technical leadership, product development, ai engineering, cloud infrastructure, distributed systems, llm orchestration, observability, experimentation, team building, personalization, natural language processing, data science, automation, user experience

Summary: Candidates should have 3-7 years of experience in machine learning engineering or applied research with strong software engineering fundamentals. A deep understanding of modern ML techniques, particularly in computer vision and NLP, is essential.

Skills: machine learning, document understanding, computer vision, natural language processing, data pipeline development, model training, ml infrastructure, technical communication, open-source collaboration, vision-language models, transformer architectures, model fine-tuning, evaluation frameworks, mlops tools, docker, kubernetes

Summary: Candidates should have extensive software engineering experience with a strong background in AI product delivery. A deep understanding of AI/ML technologies and excellent leadership and communication skills are essential.

Skills: ai engineering, leadership, software engineering, ai product delivery, project management, cloud platforms, mlops, communication, collaboration, innovation, continuous learning, technical guidance, agile methodology, stakeholder engagement, software development, machine learning, data science

Summary: Candidates should have a background in Computer Science, Mathematics, or related fields with 2-3 years of experience in AI/ML. Strong programming skills and familiarity with ML frameworks are essential.

Skills: machine learning, deep learning, artificial intelligence, python, c++, data structures, algorithms, ml frameworks, neural network architectures, training techniques, model design, model optimization, gpu acceleration, communication skills, collaboration skills

Summary: Candidates should have over 7 years of experience in web application development and at least 3 years with technologies like C# and ASP.NET Core. Experience with AI/ML models and strong analytical skills are also required.

Skills: software development, ai integration, machine learning, web applications, c#, asp.net core, angular, typescript, restful apis, cloud infrastructure, devops, agile methodologies, oop concepts, design patterns, database management, code review

Summary: Candidates must have proven experience in designing and deploying AI/ML models, with strong expertise in NLP and conversational AI. Leadership experience and proficiency in Python and ML frameworks are also required.

Skills: ai development, systems integration, evaluation & testing, leadership, team mentorship, collaboration, innovation, compliance, nlp, conversational ai, python, tensorflow, pytorch, cloud deployment, scalable systems

Summary: Candidates must have proven experience in designing, training, and deploying AI/ML models, with strong expertise in NLP and conversational AI. Proficiency in Python and ML frameworks is required, along with leadership experience.

Skills: ai development, systems integration, evaluation & testing, leadership, team mentorship, collaboration, innovation, compliance, nlp, conversational ai, python, tensorflow, pytorch, cloud deployment, scalable systems

Summary: Candidates must have proven experience in designing, training, and deploying AI/ML models, with strong expertise in NLP and conversational AI. Proficiency in Python and ML frameworks is required, along with leadership experience.

Skills: ai development, systems integration, evaluation & testing, leadership, team mentorship, collaboration, innovation, compliance, nlp, conversational ai, python, ml frameworks, cloud deployment, scalable systems

Summary: 15+ years of software engineering experience with 4+ years in customer-facing roles is required. Experience with LLM models, DevOps skills, and familiarity with FedRAMP security frameworks is preferred.

Skills: software engineering, customer-facing roles, backend development, frontend development, api design, ai-native systems, llm models, devops, cloud platforms, security frameworks, communication, federal agencies, saas integration, api management, mlops, devsecops

Summary: Candidates should have 7+ years of software engineering experience with a focus on AI/ML systems and have shipped LLM-powered features into production. Strong leadership skills and fluency in Python with experience in core ML/data libraries are essential.

Skills: ai, ml, llms, python, pandas, scikit-learn, pytorch, tensorflow, spark, prompt engineering, rag, eval frameworks, agentic workflows, system design, technical leadership, mentoring

Summary: Candidates should have Python experience, solid SQL skills, and a strong understanding of TDD principles. Experience with AI and ML technologies, particularly in LLMs and data infrastructure, is preferred.

Skills: python, data manipulation, sql, tdd, ai, ml, llm inference, embeddings, vectordbs, ranking algorithms, time series analysis, kubernetes, java, problem solving, critical thinking

Summary: A minimum of 4 years of hands-on experience in AI/ML development is required. Proficiency in Python and familiarity with modern ML/AI libraries is essential.

Skills: ai engineering, machine learning, python, api development, data pipelines, observability, cloud platforms, mlops, fastapi, flask, generative ai, prompt engineering, model monitoring, containerization, collaboration, continuous improvement

Summary: Requires Python, JavaScript, and OpenAI experience; Partner with enterprise customers to scope, integrate, and tune AI agents across workflows, delivering production-ready solutions with collaboration across product, engineering, and customer success.

Skills: python, javascript, openai, hugging face, langchain, pinecone, weaviate, llms, embeddings, prompt engineering, vector databases, rag systems, conversational ai workflows, restful apis (json), data migration, crm, erp, helpdesk platforms, developer platforms, hr systems, financial systems

Summary: The ideal candidate should have a strong background in productionizing AI/ML models and deep expertise in machine learning frameworks. Familiarity with resource-constrained environments and large-scale data processing is also essential.

Skills: machine learning, deep learning, tensorflow, pytorch, python, mlops, model optimization, deployment pipelines, onnx, tf lite, data processing, sensor data, telemetry data, algorithm development, testing, validation

Summary: 7+ years of full-time experience in AI/ML, Data, or Full Stack Software Engineering is required. Strong background in software engineering, AI/ML/NLP engineering, and data analytics/engineering is essential.

Skills: python, sql, postgresql, pytorch, ai, ml, nlp, data engineering, data analytics, cloud computing, gcp, bigquery, dbt, pandas, healthcare, compliance

Summary: 7+ years of full-time experience in AI/ML, Data, or Full Stack Software Engineering with data-intensive systems is required. Strong background in software engineering, AI/ML/NLP engineering, and data analytics/engineering is essential.

Skills: python, sql, postgresql, pytorch, ai, ml, nlp, data engineering, data analytics, cloud computing, gcp, bigquery, dbt, pandas, healthcare, compliance

Summary: The ideal candidate is a self-motivated, product-minded software engineer with deep expertise in applying LLMs to production environments. Proven ability to work in a highly collaborative, product-focused environment is essential.

Skills: ai engineering, large language models, prompt engineering, typescript, python, feature development, coding, integration, retrieval-augmented generation, vector databases, automated testing, evaluation frameworks, user experience, data pipelines, collaboration, asynchronous communication

Summary: Candidates should have 3+ years of engineering or technical deployment experience, ideally in customer-facing or government environments. Strong backend engineering skills and familiarity with generative AI systems are essential, along with excellent communication skills.

Skills: backend engineering, python, typescript, apis, data processing, etl pipelines, generative ai, context engineering, kubernetes, cloud environments, information retrieval, sql, nosql, communication skills, mission-oriented mindset, technical deployment

Summary: The ideal candidate should have a Bachelor's Degree and at least 5 years of experience in relevant fields. Hands-on experience with Azure Cognitive Search and proficiency in programming languages such as .NET, Python, or JavaScript is required.

Skills: azure cognitive search, ai/nlp services, semantic search, natural language understanding, recommendations, data indexing, query optimization, search analytics, cloud architecture, rest apis, microservices, devops practices, ci/cd pipelines, agile methodologies, project management tools, communication skills

Summary: Candidates should have 8+ years of software engineering experience, with a focus on AI/ML systems development. Proven expertise in AI/ML Ops and experience leading teams on complex technical initiatives is essential.

Skills: ai/ml systems development, multi-agent orchestration, llm-based systems, ai/ml ops, distributed systems, model evaluation methodologies, team leadership, technical communication, python, full-stack development, node.js, typescript, security, compliance, ethical ai practices

Summary: Founding AI Engineer to build real-time voice models, memory/personalities, and low-latency pipelines; top tech: react, next.js, node.js.

Skills: react, next.js, node.js

Summary: 8+ years of experience as a software engineer with expertise in system architecture and strong backend foundation. Experience implementing secure systems and ability to balance strategic thinking with hands-on execution.

Skills: ai engineering, system architecture, backend development, node.js, python, javascript, cloud technologies, aws, security solutions, api integrations, devops, infrastructure-as-code, cross-functional collaboration, full-stack development, reliability engineering, scalable software

Summary: Candidates must have a Bachelor's or Master's degree in a quantitative discipline with significant experience in Python-based application development and machine learning. Familiarity with generative AI technologies, data manipulation libraries, and cloud platforms is also required.

Skills: python, machine learning, generative ai, large language models, apis, data pipelines, cloud platforms, containerization, ci/cd, deep learning, natural language processing, data manipulation, version control, software development, problem solving, collaboration

Summary: Candidates must have a bachelor's degree in a technical field and at least 8 years of experience in IT, including 5 years in a relevant discipline. Leadership experience and strong project management skills are essential.

Skills: ai engineering, leadership, project management, machine learning, cloud computing, aws, azure, software development, agile practices, devops, mlops, data governance, security, compliance, team collaboration, vendor management

Summary: Internship focused on AI, ML, and full-stack development. Skills needed: React, Python, and machine learning technologies.

Skills: react, python, machine learning

Summary: Minimum of 2 years experience in AI/ML development, data science, software engineering, or relevant experience is required. Proficiency in programming languages such as Python or Java and familiarity with data engineering tools and platforms is preferred.

Skills: python, java, data engineering, machine learning, tensorflow, pytorch, sql, data analysis, collaboration, communication, predictive maintenance, anomaly detection, iot devices, gis data, data visualization, cloud services

Summary: Candidates must have a minimum of 6 years of experience in AI/ML development or related fields, along with strong programming skills in languages such as Python, R, or Java. A bachelor's degree in a relevant field is preferred, and familiarity with railroad operations is a plus.

Skills: python, r, java, machine learning, deep learning, data engineering, cloud services, sql, nosql, mlops, generative ai, data pipelines, vector databases, analytical skills, problem-solving, communication

Summary: Seeking a Principal AI Engineer to build AI infrastructure and tools, champion AI adoption. Requires expertise in Python, TypeScript, and AI frameworks.

Skills: python,, typescript

Summary: The ideal candidate should have strong programming skills in Python and experience with machine learning fundamentals and deploying models in production. Knowledge of prompt engineering techniques and experience with agentic AI systems are essential.

Skills: python, machine learning, neural networks, prompt engineering, agentic ai, large language models, sql, gcp, optimization, data processing, ai systems, collaboration, technical documentation, feedback, problem solving, communication

Summary: Candidates must have over 5 years of experience building and scaling production ML systems with measurable business impact. A strong background in ranking algorithms and proficiency in Python and ML frameworks is essential.

Skills: machine learning, recommendation systems, ranking algorithms, python, tensorflow, pytorch, sql, data warehouses, data lakes, distributed computing, a/b testing, feature engineering, data pipelines, real-time personalization, statistical testing, model monitoring

Summary: Candidates must have 5+ years of software development and ML engineering experience, with 3+ years focused on advertising systems. Proven experience optimizing ad performance using mature models and emerging ML technologies is essential.

Skills: machine learning, advertising systems, optimization, recommendation systems, advertising algorithms, nlp, cv, python, sql, tensorflow, pytorch, distributed data processing, cloud infrastructure, analytical problem-solving, communication, teamwork, project management

Summary: Candidates must have 7+ years of software development and ML engineering experience, with at least 3 years focused on advertising systems. Proven experience in optimizing ad performance and expertise in ML areas such as recommendation systems and advertising algorithms is essential.

Skills: machine learning, advertising systems, optimization, recommendation systems, advertising algorithms, nlp, cv, python, sql, tensorflow, pytorch, distributed data processing, cloud infrastructure, analytical problem-solving, communication, project management

Summary: Candidates must have over 7 years of experience in building and scaling production ML systems with measurable business impact. A strong background in ranking algorithms and proficiency in Python and ML frameworks is essential.

Skills: machine learning, recommendation systems, python, tensorflow, pytorch, sql, data warehousing, distributed computing, a/b testing, ranking algorithms, feature engineering, data pipelines, real-time personalization, experimentation, data processing, collaboration, analytical thinking

Summary: Intern developing LLM applications with Python, React, and Node.js. Participate in projects impacting the Poe product and enhancing user experiences.

Skills: python,, react,, node.js

Summary: Seeking an AI Engineer to prototype, wire APIs, and launch products using Python, TypeScript, and vector databases.

Skills: python,, typescript

Summary: Candidates should have 5+ years of software engineering experience, with at least 2 years focused on AI systems and deep expertise in LLM implementation. A strong foundation in TypeScript and experience with modern AI frameworks and tools are also required.

Skills: ai systems, llm implementation, software engineering, typescript, document analysis, legal reasoning, ai development, technical leadership, mentoring, prototyping, integration, evaluation, structured reasoning, tool-use pipelines, problem solving, continuous learning

Summary: The position requires 7+ years of experience writing ML code for launched products and experience leading a small team of developers. Strong programming skills in Python and an understanding of the state of the art in generative AI are essential.

Skills: machine learning, generative ai, python, llms, data sets creation, backend api services, mentoring, cross-functional collaboration, ml models, pydantic ai, vector databases, microservices architectures, data pipelines, tensorflow, pytorch, sql

Summary: Candidates should have 7+ years of experience writing ML code for launched products and experience leading a small team of developers. A strong understanding of generative AI and experience with LLMs is essential.

Skills: machine learning, generative ai, python, llms, data engineering, api services, mentoring, prototyping, backend development, microservices, distributed systems, tensorflow, pytorch, scikit-learn, sql, data pipelines

Summary: The position requires 7+ years of experience writing ML code for launched products and experience leading a small team of developers. A strong understanding of generative AI and programming skills in Python are essential.

Skills: machine learning, ai features, generative ai, python, team leadership, backend api services, ml models, data sets creation, pydantic ai, vector databases, nodejs, java, kotlin, tensorflow, pytorch, scikit-learn, sql

Summary: The position requires 7+ years of experience writing ML code for launched products and experience leading a small team of developers. A strong understanding of generative AI and proficiency in Python are essential.

Skills: machine learning, ai development, python, generative ai, backend api services, ml models, data sets creation, team leadership, agile methodologies, cross-functional collaboration, prototyping, mentoring, microservices, data pipelines, tensorflow, pytorch

Summary: Candidates should have a Bachelor's or Master's degree and at least 6 years of software development experience, including 3 years in a technical leadership role. Proficiency in developing cloud services using .NET and experience with Python and machine learning libraries is essential.

Skills: software development, technical leadership, cloud services, python programming, machine learning, software architecture, microservices, cloud computing, agile methodologies, devops practices, containerization, kubernetes, docker, ci/cd pipelines, problem solving, communication skills

Summary: Candidates should have over 5 years of full-stack development experience, including 2 years with AI/ML technologies in production. Strong skills in frontend and backend development, API design, and familiarity with cloud technologies are essential.

Skills: full stack development, ai/ml technologies, typescript, javascript, react, go, python, api design, service architecture, cloud technologies, database systems, data processing pipelines, containerization, orchestration technologies, monitoring, versioning, observability

Summary: Candidates should have 3+ years of experience in machine learning, deep learning, or applied AI, along with strong Python skills. Familiarity with big data tools and cloud environments is also preferred.

Skills: machine learning, deep learning, python, tensorflow, pytorch, jax, mlops, cloud environments, docker, kubernetes, big data, feature engineering, ai strategy, data pipelines, real-time processing, batch processing

Summary: Extensive experience with the full Elasticsearch stack and SQL database technologies is required. Familiarity with AWS, Python, and Agile methodologies is also essential.

Skills: data engineering, sql, nosql, elasticsearch, aws, linux, docker, kubernetes, python, agile, natural language processing, machine learning, data storage, data retrieval, security best practices, data analysis

Summary: Build and scale medical claims auditing infrastructure using distributed systems, data pipelines, and APIs. Requires experience in React, Node.js, and SQL.

Skills: react, node.js, sql