Top Machine Learning Engineer Jobs

As a Founding Data Scientist, you will develop predictive models and optimize data infrastructure to enhance supply chain operations, focusing on shipment risk and decision-making.

Integrate state-of-the-art machine learning (especially generative) into production-grade sensor simulation for LiDAR, Radar, and Camera. Collaborate with research, rendering, and physics teams to develop, evaluate, and deploy models and tooling that produce production value and customer impact.

Develop, prototype, evaluate, and deploy ML-first behavior prediction and planning models to forecast motion and interactions of road users. Build software and infrastructure for behavior-specific ML, collaborate with perception and planning teams, and productionize models for autonomy systems.

Develop, train, fine-tune, and deploy AI/ML models (including LLMs and generative AI). Build user-facing AI applications (chatbots, virtual assistants), optimize model performance, run experiments (prompt engineering, RAGs, fine-tuning), integrate solutions with systems, ensure data privacy/security, and brief stakeholders. Support big-data approaches and collaborate across teams.

Build and deploy ML models and pipelines for entity resolution and a knowledge graph at scale. Fine-tune algorithms, expand data ingestion and enrichment, create evaluation harnesses, and integrate agentic workflows to support research and product teams processing tens of millions of records daily.

Design, prototype, and productionize AI systems and infrastructure—recommendations, natural language interfaces, agentic workflows—partnering with product and engineering to scale ML across the full lifecycle (data curation, training, deployment, monitoring).

Build and productionize AI systems and infrastructure that power customer-facing features and internal tooling. Partner with product, design, and engineering to identify high-impact ML opportunities, prototype solutions (recommendations, NL interfaces, agents), and manage the full ML lifecycle from data curation to deployment and monitoring.

Design, prototype, and productionize AI/ML systems (recommendations, NL interfaces, agentic workflows). Build and scale ML infrastructure, partner with product/design/engineering, and solve UX problems at the intersection of AI and BI.

Design, prototype, and productionize AI systems (recommendations, natural language interfaces, agents). Partner with product and engineering to identify AI opportunities, build scalable ML infrastructure, and manage the full ML lifecycle from data curation through training, deployment, and monitoring.

Design, implement, and validate autonomy software for mining vehicles including perception, localization, mapping, motion planning, and control. Integrate and calibrate LiDAR, camera, radar, IMU/GNSS sensors; build embedded real-time software; develop simulation and data pipelines; and lead bench, rig, and field validation while collaborating with hardware and controls teams.

Develop and deploy perception algorithms and analytics for re-identification and productivity/safety metrics on large construction sites. Integrate raw sensor data (camera, lidar, IMU), adapt perception signals for customer-facing analytics, work with customers to scope capabilities, and deploy models to fleets of machines while designing evaluations and analyzing sensor data.

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

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

Develop, deploy, and maintain deep learning perception models for autonomous delivery drones. Build resource-constrained real-time inference, improve existing models and pipelines, and collaborate with hardware, software, and flight-test teams to productionize safe, reliable perception features.

Design, develop, and deploy machine learning and deep learning models; build end-to-end ML pipelines including preprocessing, training, evaluation, and deployment; perform feature engineering on large datasets; deploy and monitor models on cloud platforms; collaborate with cross-functional teams to integrate AI solutions and retrain models as needed.

Design, build, and deploy production-grade ML and AI systems end-to-end, combining classical ML, deep learning, and LLM/agentic integrations. Implement MLOps, monitoring, CI/CD, model serving, vector search/RAG pipelines, and scalable APIs; mentor engineers and drive engineering best practices.

Design, develop, and deploy production 3D and BEV perception ML models for autonomous trucks. Own end-to-end model lifecycle from data prep, training, evaluation, and deployment. Improve model robustness, performance, and generalization across sensor modalities. Integrate models with autonomy software, enhance training pipelines and tooling, analyze failures, and mentor junior engineers.

The Machine Learning Engineer will design, develop, and implement advanced recommendation systems, collaborating with cross-functional teams to enhance personalization for a global audience.

Apply deep learning to improve quality and accuracy of labeled multi-modal sensor data for simulation. Build models to identify and correct perception-data issues, analyze data quality and anomalies, collaborate with perception and simulation teams, and lead ML strategies for high-fidelity data generation and labeling pipelines.

As a Staff Computer Vision AI/ML Engineer, you will lead a team to develop and deploy AI/ML algorithms in remote sensing, including analyzing datasets and training deep learning models.

Lead design and deployment of scalable auto-labeling pipelines and automated graders. Train, optimize, and productionize state-of-the-art 2D/3D computer vision models and VLMs. Set ML strategy, mentor engineers, and collaborate with Perception, Planner, and Simulation teams to meet labeling needs.

Lead technical development of machine learning algorithms for the onboard Planner, advancing imitation learning, reinforcement learning, and model scaling; integrate foundation models; create metrics, data, and training frameworks; mentor ML developers; and collaborate across perception, simulation, system design, and safety teams to solve autonomous driving challenges in complex urban environments.

Design, train, and implement domain-specific LLMs for automation in restoration companies. Collaborate with teams, coordinate AI engineering, and ensure model reliability.

Lead ML Engineer for Finance Tech to design, build, deploy, and maintain AI/ML systems (including LLMs and RAG). Partner cross-functionally to create production data pipelines, model evaluation, governance, observability, and responsible AI practices while contributing technical vision and scaling AI infrastructure.

Develop and productionize AI features from PoC to scalable deployments. Write production-ready Python code, implement testing and debugging, refine user stories, participate in ethical and security reviews, and collaborate with stakeholders to align AI solutions with business needs.