Top AI & Machine Learning Jobs

Implement and evaluate machine learning models, manage model training and deployment, design data pipelines, build integrations and low-code solutions using AI-assisted tools, and ensure data governance and security while partnering with legal and technology stakeholders.

Implement and deploy machine learning models, design data pipelines and integrations, build low-code AI-enabled legal workflow tools using tools like GitHub/Microsoft Copilot, ensure data governance and secure integrations, collaborate with Legal and tech stakeholders, and contribute to research, documentation, and continuous improvement.

Build and operate scalable Golang backend services and APIs for a multimodal ML platform handling video, image, and document processing. Integrate ML/LLM inference, agentic workflows, and vector retrieval (Milvus). Deploy and manage services on Kubernetes with Terraform on AWS, ensure observability, reliability, and security, and collaborate with ML engineers to productionize pipelines and run on-call/incident response.

Lead architecture and roadmap for large-scale ML platforms powering search, ranking, and recommendations. Build and deploy distributed, real-time ML systems, translate research into production, advance recommender and generative AI capabilities, mentor engineers, and drive cross-functional ML initiatives aligned with business goals.

Develop and deploy machine learning algorithms, evaluate their performance, improve ML systems, and collaborate with cross-functional teams.

The role involves designing and implementing machine learning systems, mentoring engineers, leading technical strategies, and ensuring system reliability and scalability.

Develops and deploys machine learning algorithms, evaluates their accuracy, creates data pipelines, and contributes to innovations and technical documentation. Guides less experienced colleagues and collaborates across teams.

The role involves designing evaluation pipelines for AI agents, establishing benchmarks for performance, and collaborating with product teams. Responsibilities include dataset management, automated evaluations, and mentoring junior engineers.