Ai Developer Jobs with Salary ≥ 200k

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 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: 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: 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: 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: 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 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: 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