Top Machine Learning Jobs

As a Machine Learning Engineer, you will fine-tune transformer models, deploy machine learning solutions, and work with cross-functional teams on innovative projects.

As a Staff ML Engineer, you'll lead complex model quality improvements in clinical AI, spanning research and engineering, optimizing performance under high compliance conditions.

The Staff ML/AI Platform Engineer will design, prototype and deploy AI/ML models, optimize pipelines, mentor junior engineers, and collaborate closely with other teams to develop machine learning solutions.

Lead and oversee enterprise ML and statistical modeling efforts, build and mentor data science teams, ensure model governance and compliance, collaborate cross-functionally to deliver scalable AI solutions that drive business outcomes, and advance research and adoption of cutting-edge ML methods.

Design, build, and deploy AI/ML capabilities (LLMs, RAG, embeddings, vector search) into secure cloud environments to accelerate cyber analyst workflows. Integrate models with APIs, monitor performance and drift, support retraining, perform experiments/AoAs, and provide stakeholder training and operational guidance in government settings.

Research and develop machine learning algorithms and software prototypes for sponsor problems. Perform data collection, modeling, fusion, visualization, statistical analysis, and present technical reports. Collaborate with staff, supervise junior personnel and students, and integrate ML prototypes into research and pre-production environments.

Lead the design and delivery of complex ML systems, architect integrations, and set high standards for engineering practices while collaborating with teams to develop robust solutions and mentor other engineers.

The Staff Machine Learning Engineer will design and deliver complex ML systems, lead integration efforts, build scalable solutions, and optimize model deployments, collaborating with various teams and mentoring peers.

Develop and deploy AI/ML methods (including LLMs/agentic AI) for tuning, diagnosis, control, and automation of particle accelerators. Test methods experimentally on the APS injector and upgraded storage ring, support operator decision-making, automate workflows, and analyze beam and system data.

Support SMEs to identify, evaluate, and integrate AI/ML capabilities (especially for waveform analysis) into workflows. Provide integration guidance, documentation, training, troubleshooting, and cross-functional collaboration. Support data analysis and build Power BI dashboards, enabling data-driven decisions in a DoD environment. Requires active clearance and stakeholder enablement.

Design, develop, and deploy machine learning models and data pipelines for naval applications. Build and optimize distributed, cloud-native analytics and event-streaming systems, work with multiple data formats and GIS tools, containerize and monitor deployments, apply DoD security practices, and collaborate with multidisciplinary teams to deliver mission-ready AI solutions in shipboard and operational Navy environments.

Own Coinflow's ML layer: explore transaction and behavioral data, build production models and decisioning systems, establish ML/data practices, define core metrics, and partner with Engineering, Product, and Operations to embed intelligence into products and tooling.

Lead and grow a small ML team to turn Evvy's vaginal microbiome dataset into validated, product-ready diagnostic and prognostic models. Drive technical quality, roadmap planning, cross-functional translation, model validation and deployment readiness, hiring, and day-to-day team management.

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.

As an AI/ML Data Contributor, you will perform tasks like data labeling and content evaluation, contributing to machine learning model improvements across various projects.

The role involves data labeling, annotation, content evaluation, and testing to enhance machine learning models, requiring attention to detail and basic computer skills.

As an AI/ML Data Contributor, you will assist in data labeling, evaluation, testing, and follow project guidelines while ensuring quality task completion.

Assist in improving machine learning models through data labeling, content evaluation, and user-based testing tasks, both remote and on-site.

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.

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.

Lead design, development, and delivery of ML, DL, and Generative AI systems for production. Apply prescriptive analytics, optimization, recommendation, and reinforcement learning. Build and evaluate models, run experiments, develop prototypes, benchmark methods, and collaborate with business partners to translate data into actionable recommendations and influence strategy.

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.

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, 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.