Top AI & Machine Learning Jobs

Join the AI team to develop and deploy real-time perception and deep learning models for autonomous vehicles. Build and optimize data pipelines, research object detection, segmentation, road understanding, motion prediction, and apply multi-modal sensor fusion for robust onboard perception.

Lead enterprise data science strategy, roadmap, and governance. Prioritize high-impact use cases, oversee model lifecycle and MLOps, establish responsible AI standards, manage teams and budgets, and communicate outcomes and risks to executives to drive measurable ROI and adoption.

Lead long-horizon R&D to define future decision intelligence: explore reasoning architectures, prototype and formalize system primitives, evaluate new signal classes, and translate research into reusable components aligned to strategic product direction.

Design and build production-quality medical AI systems, own end-to-end problems, prioritize rigorous evaluation and quantitative proof, collaborate across products, and deliver high-impact, deployed outcomes in a fast-paced, hands-on engineering culture.

Lead relevance evaluation and quality improvements by fine-tuning LLMs, building low-latency reranking and filtering systems, scaling LLM deployments, creating automated monitoring pipelines and agentic insights, and validating impact via A/B tests while collaborating with cross-functional teams.

Design, build, and deploy AI-powered applications, automations, dashboards, and integrations to improve operational efficiency. Evaluate LLMs and automation platforms, create data-driven BI tools, integrate systems via APIs and cloud services, train staff on AI tools, and establish governance and strategy for responsible AI use.

Design, implement, and optimize ML and deep learning models; preprocess and prepare large datasets; integrate models into production; monitor and maintain model performance; collaborate with engineers and stakeholders; stay current on ML/AI advances.

Build and ship AI prototypes applying computer vision and large language models to construction problems. Own an intern project end-to-end, iterate with contractor and architect feedback, and deploy models in production while doing hands-on, messy domain work.

Design and deploy scalable production ML systems powering Diffbot's Knowledge Graph. Improve model accuracy via research, feature engineering, and hyperparameter tuning; own end-to-end performance for 60+ ML problems; assess new research for production feasibility; collaborate on training data and error analysis with product and customers.

Develop hybrid, process-informed ML models and virtual sensors with process engineers; own end-to-end data science from feature engineering to production deployment, monitoring, and maintenance; engage customers and cross-functional teams for adoption.