Top AI & Machine Learning Jobs

Develop and maintain large-scale evaluation, introspection, and visualization tools for autonomous vehicle ML models. Build metrics, dashboards, and pipelines that process billions of examples, collaborate with data, infra, simulation, and modeling teams, and provide technical leadership to align offline evaluation with real-world AV behavior.

Design, build, and deploy scalable ML training and evaluation platforms for autonomous driving. Lead architecture and implementation of distributed, high-performance pipelines, drive cross-team prioritization, mentor engineers, and support recruiting and code quality to accelerate ML model development lifecycle.

Develop and implement validation methods, tools, and production code to analyze autonomous vehicle behavior using simulation and test data. Build scalable testing products, generate data-driven insights for AI and systems engineers, and establish validation best practices across teams.

Lead development and productionization of advanced forecasting and predictive models: assess existing analytics, define data needs, design methodologies, run proofs-of-concept, architect cloud-based model deployments, and monitor model performance while translating results for business stakeholders.

The Senior Systems Data Scientist will develop methodologies for measuring trust in AV testing, manage data analysis frameworks, collaborate with teams, and provide insights for decision-making.

Design and deliver enterprise-grade AI workflow transformations on GCP. Build secure, event-driven backend services and multi-step AI agents, integrate bots with enterprise systems, implement telemetry, testing, CI/CD, HITL validation, and create reusable architecture, documentation, and runbooks while guiding adoption and governance.

Design, build, and scale AI-enabled workflow and automation solutions across collaboration platforms and enterprise systems. Translate manual processes into secure, reusable, event-driven automations using Python/JavaScript, integrate AI capabilities like Gemini, implement logging and telemetry, and partner with product, security, and business teams to deploy and sustain enterprise transformation solutions.

Hands-on Staff Data Scientist to translate ambiguous business problems into production-grade ML solutions. Responsibilities include feature engineering, model development, evaluation, MLOps, deployment, monitoring, experimentation, cross-functional partnership, and technical leadership to scale reproducible data-science practices and deliver measurable business impact.

Lead design, architecture, and deployment of end-to-end ML solutions for onboard autonomous driving. Apply foundation-model alignment, unsupervised pre-training, imitation and reinforcement learning, and scale large-model training pipelines. Collaborate cross-functionally, mentor engineers, conduct research, and productionize foundation models for safe, reliable real-world driving.

Build and deploy scalable ML training and evaluation platforms, drive technical projects and architectural decisions, collaborate with partner teams, prioritize platform improvements, ensure reliability and performance, and mentor junior engineers.