Top AI & Machine Learning Jobs

As an ML Engineer, you'll deploy models and create tailored AI solutions for clients, ensuring impactful integrations and customer success.

Design and build scalable end-to-end ETL/ELT data pipelines, process log and semi-structured data with Python and dataframes, and architect scalable database schemas (partitioning/sharding). Ensure data traceability, validation, monitoring, and enable datasets for machine learning model training and deployment while collaborating with data scientists and engineering teams.

Open call to join an early-stage, YC-backed startup building compliant conversational voice and video AI for life sciences. Applicants should submit a brief intro, the type of work they do best, and why they care about life sciences AI. Company emphasizes ownership, autonomy, rapid iteration, AI-first tooling, competitive compensation, and equity.

The ML/LLM Engineer will optimize pipelines for ML and LLM systems, fine-tune models, collaborate on healthcare applications, and enhance model quality and safety.

Build the core platform: design scalable systems to process contracts, develop agentic AI/LLM tools for contract review, set technical priorities with founders, establish maintainable codebase, and recruit/mentor engineers.

The Data Scientist will analyze complex data sets, manage data consistency, create visualizations, build mathematical models, and communicate findings effectively.

Build and ship features on an AI-native platform using Claude Code. Translate requirements into production code, review and refine AI-generated code, write automated tests, document APIs and architecture, participate in async code reviews, and identify technical debt.

Lead design and implementation of a production inference platform for LLMs. Define roadmap, integrate and optimize inference runtimes, manage GPU infrastructure, and build systems for deployment, autoscaling, observability, and operational excellence. Benchmark models/runtimes, partner with ML and product teams, make architectural tradeoffs, and mentor engineers to scale AI infrastructure.

The role involves designing and implementing machine learning systems for knowledge representation and temporal reasoning, focusing on organizational intelligence. Responsibilities include building LLM-powered pipelines, developing memory algorithms, and researching various ML techniques.

Lead product prioritization and execution for AI-driven tools that automate contractor front-office tasks. Partner with customers to discover automation opportunities, define specs, and work with engineering and design to launch AI agents integrated with systems like ServiceTitan.