Top Machine Learning Jobs

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

Conduct ML and deep learning research to build, test, and deploy predictive models for trading. Collaborate with traders, researchers, and engineers to engineer features, preprocess data, prototype algorithms, and improve production research tooling to enhance trading performance.

Lead development and deployment of ML models for trading, drive research and prototyping, oversee data and feature engineering, mentor researchers, and build scalable ML research infrastructure.

Design, build, and productionize machine learning models and data pipelines for recommendation, bidding, and forecasting. Collaborate with product and engineering teams, evaluate and monitor model performance, maintain high-quality tested code, prototype research ideas, and run experiments. Hybrid schedule: four days in-office, one remote.

Lead design and deployment of production-grade ML systems (ranking, retrieval, LLMs). Drive architecture decisions, run experiments and evaluations, build scalable feature pipelines and monitoring, mentor engineers, and collaborate cross-functionally to integrate AI into products and scale ML capabilities.

Lead design, build, deploy, and maintain production ML and AI systems (including LLM inference, RAG, similarity search, observability, and governance). Collaborate cross-functionally to create data pipelines, retrain and monitor models, and apply responsible, explainable AI practices while contributing technical vision and roadmap for AI solutions.

The Senior Machine Learning Scientist will lead the development of ML systems for personalized CRM marketing, define technical roadmaps, and mentor team members while collaborating with cross-functional teams.

Lead research, design, and deployment of large-scale search and recommendation ML systems. Build multi-modal retrieval and multi-stage ranking pipelines, advance intent understanding and personalization, develop sequential recommenders, design offline/online evaluation (A/B testing, counterfactuals), collaborate with engineering/product teams, and mentor scientists to productionize cutting-edge AI solutions.

Design, train, and deploy machine learning models for detecting malicious content, working with large datasets and collaborating with teams to enhance system scalability.

Lead finance transformation by driving AI adoption and implementing ML solutions for forecasting and anomaly detection. Optimize processes, decommission legacy workflows, ensure data integrity across ERPs, craft LLM prompts, upskill finance teams, manage projects using Airbus methodology, and enforce compliance and auditing for AI-driven automation.

Lead the development and implementation of machine learning solutions, managing a team to drive strategic decisions and innovative business outcomes.

Develop, validate, and deploy biomedical ML and deep learning algorithms on sensor data. Own end-to-end lifecycle from data curation to embedded/cloud deployment, run clinical study design and statistical validation, and collaborate with cross-functional R&D, firmware, and software teams.

Develop, evaluate, and optimize ML models (NLP, computer vision, statistical methods) for large-scale unstructured data. Collaborate with engineering, product, and research teams to design, deploy, and maintain scalable, robust predictive systems and data pipelines. Research state-of-the-art methods, integrate new data sources, provide technical leadership, and participate in on-call rotation to ensure model availability.

Lead multi-year vision and roadmap for AI/ML recommendation and prediction products. Align executives, prioritize using data and research, and guide engineering to deliver scalable ML features. Evangelize AI product standards, mentor other PMs, and partner with design, data science, and engineering through the full delivery lifecycle.

Set the multi-year vision and roadmap for AI/ML recommendation and prediction products. Secure executive alignment, prioritize via data and research, mentor PMs, and partner with design, data science, and engineering to deliver production ML features on schedule.

Set multi-year vision and roadmap for AI/ML recommendation and prediction products. Align executives, prioritize investments, partner with design, data science, and engineering to ship ML features, mentor PMs, and drive org-wide AI/ML product standards and strategy.

Design, build, and deploy AI and machine learning solutions at scale. Develop data pipelines and scalable models, perform data wrangling and analysis, apply NLP and neural networks, collaborate with clients and teams, and contribute to open-source and iterative improvement of AI systems.

Develop ML and multimodal AI systems that integrate neurophysiological, behavioral, and sensor data for cognitive state estimation and decision support. Build algorithms and prototypes, apply cognitive science to improve explainability and human-AI collaboration, contribute to proposals/publications, and demonstrate capabilities for mission-driven R&D.

Develop and automate Python-based ETL and data pipelines in Databricks; clean and preprocess manpower/personnel data; build, train, and deploy machine learning models; create Qlik/Tableau reports and dashboards; maintain historical data and troubleshoot ETL; produce documentation and data products; collaborate with cross-functional teams to translate requirements into data-driven solutions.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

Lead and mentor ML engineers and data scientists, overseeing ML strategy and development of scalable models for healthcare applications.

Develop and deploy machine learning models for national security challenges. Responsibilities include algorithm development, model training, deployment, and collaboration with teams for effective ML solutions.

Lead and grow the Machine Learning Engineering team, set technical direction, define team roadmap, and collaborate across product and engineering teams.

Train personalized ML models, create synthetic data pipelines, evaluate model quality, and develop safeguards for AI privacy and misuse.

The Senior Staff Machine Learning Engineer will improve Coupang's search and discovery systems using advanced algorithms, addressing bottlenecks, proposing solutions, and leading projects involving personalization and recommendations.