Top Machine Learning Engineer Jobs

Design and build machine-learning-driven robotic systems that operate in the real world, support portfolio company growth, influence product and technical direction, and advance company and career outcomes.

Senior Machine Learning Engineers will develop ML products and lead projects end-to-end—from initial concept through final launch—across S32 portfolio companies. Candidates should drive product direction, have strong ML engineering and productization experience, and make significant business impact.

Build scalable ML data pipelines for Waabi's autonomous driving platform. Design, optimize, and manage datasets and training processes while collaborating with scientists and engineers.

As an AI/ML Platform Engineer, you will develop APIs, data pipelines, and workflows to support AI capabilities for scientific research, ensuring system reliability and scalability.

Lead architecture and productionization of scalable ML/LLM systems for legal products. Build LLM applications (RAG, agents), hybrid search, APIs, streaming/data pipelines, containerized deployments, and observability. Partner with data scientists to turn models into reliable, low-latency customer-facing services and establish reusable frameworks, best practices, and technical leadership across teams.

Build and productionize large-scale data pipelines and platforms to generate ML and evaluation datasets from driving logs and simulation data. Design tools for data mining, exploration, and analysis, and collaborate with Data Science and Quantitative Analytics to deliver high-impact, production-ready infrastructure and dataset generation.

Lead ML Performance Optimization for autonomous driving, collaborating across teams, implementing optimization techniques, and mentoring engineers for career growth.

Design and develop auto-labeling algorithms for autonomous driving, collaborating with ML engineers to enhance data quality and efficiency in model training.

Develop spatio-temporal machine learning models for automated driving, collaborate with experts on algorithm design, and ensure production-level implementation of perception systems.

Design and deploy end-to-end machine learning solutions: gather/process large datasets, build predictive and topic-modeling systems, develop data pipelines, use AWS and NLP APIs, containerize and deploy models, lead technical teams, and manage project delivery and stakeholder communication.

Design and build the intelligence layer: retrieval and memory systems, RAG pipelines, feedback and evaluation loops, RL and fine-tuning experiments, LLM integration, observability for AI performance, and collaborate to productize AI features.

Design, train, and deploy manipulation policies (imitation learning, RL, behavior cloning) for deformable food handling. Build data collection pipelines, evaluation metrics, and recovery behaviors. Partner with perception and robotics teams to validate end-to-end grasp-to-place performance and iterate policies on physical robots in production.

The Senior Machine Learning Engineer will lead the perception stack, focusing on detection, tracking, classification, and sensor fusion for targeting systems, with responsibilities including model development and real-time optimization on embedded devices.

As a Senior Software Engineer, you'll develop machine learning models and software applications, translating technical requirements into solutions while ensuring excellence in product delivery.