Top Hybrid Machine Learning Engineer Jobs

Build and own Clera’s AI/ML intelligence layer, including recommendation systems, ranking algorithms, and LLM-powered candidate-role matching. Develop production-ready features, data pipelines, and services while collaborating cross-functionally and shipping frequently. The role requires hands-on experience with the listed development tools, TypeScript, React, startup environments, and a willingness to work six days per week in a San Francisco hacker house.

Lead the technical direction for ML-powered experimentation and predictive insights. Build production systems spanning modeling, LLMs, retrieval, simulation, statistical methods, data pipelines, backend services, and product workflows. Develop traceable, calibrated, privacy-aware predictions; establish rigorous evaluation, backtesting, monitoring, and abstention practices; and translate insights into approval-gated experimentation workflows. Partner with engineering, product, data science, and research teams while providing technical leadership for high-quality production ML.

Own the quality and behavior of AI-generated interactive content. Build evaluation systems using production creator data, develop agentic ML systems that turn ideas into playable games, debug failures across models and pipelines, run rigorous experiments, and help establish the AI team’s technical standards and direction.

Research Engineer responsible for developing, training, evaluating, and deploying healthcare AI models and pipelines for conversational voice agents. The role focuses on instruction following, tool calling, retrieval, memory, speech and audio research, model optimization, benchmarking, failure analysis, and production integration. Candidates should have 5+ years of experience, including AI/ML engineering or research, production LLM deployment, Python proficiency, and a record of converting research prototypes into reliable measurable improvements.

The Senior Applied Scientist will design and optimize credit risk models using machine learning, collaborating with cross-functional teams to translate business problems into technical solutions and drive scalable risk decisions.

Design, build, evaluate, and deploy scalable AI models for insurance business problems. Analyze large datasets, validate models, monitor performance, and collaborate with data scientists and engineers to align solutions with business objectives and communicate results to non-technical stakeholders.

Lead and contribute to Waymo’s planet-scale ML data infrastructure and inference platform. Partner with modeling teams to manage data quality, distributions, freshness, feature stores, and ML flywheels. Mentor engineers, lead complex cross-functional projects, and support scalable data stores, model hosting, bulk and online inference, and high-QPS production services.

Build and productionize computer vision and machine learning systems that convert video into reliable workplace safety incidents. Responsibilities include designing Flink-based perception pipelines, training and optimizing models with Triton and TensorRT, implementing tracking and probabilistic reasoning, improving latency and cost, building observability and evaluation systems, integrating ML tooling, and partnering with platform, customer success, GTM, and data operations teams on deployments and data quality.

Leads AI and machine learning data engineering development projects, including global initiatives. Manages resources and development teams, improves quality and engineering practices, provides subject matter expertise, develops business plans, mitigates risks, handles escalations, and drives technology innovation and change management.

Embed with grocery customers to scope, integrate, and deploy production LLM- and agent-powered systems. Build and harden platform components (knowledge graph/ontology, retrieval, agent frameworks, serving, evals, and observability) so field learnings become reusable tooling. Balance customer-facing implementation with platform engineering to enable scalable, reliable AI in production.