Top Machine Learning Jobs

Oversee strategic development and execution of analytics and machine learning initiatives. Mentor teams, manage projects, enforce data governance, and collaborate cross-functionally.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

The Lead Machine Learning Engineer will design and deploy ML models, optimize AI systems, and collaborate with cross-functional teams to enhance banking solutions.

The Senior Manager, Machine Learning will lead a team of ML engineers and scientists to develop and implement machine learning systems, ensuring they meet product needs and are scalable.

Lead and build a Machine Learning team, driving strategy and execution across product areas like Document Generation and Voice Agents while collaborating with Product and Engineering.

As a Machine Learning Research Engineer, you'll create critical AI features for the Archie product, collaborating with experts and transitioning AI prototypes into real-world applications. You'll develop AI tools for engineering design and work closely with research scientists.

Join Capsule as an AI Engineer to develop ML models for video editing. Responsibilities include researching ML techniques, collaborating on feature development, and optimizing model performance.

As a Staff Machine Learning Engineer, you'll design large-scale recommendation and retrieval systems, enhance quizlet's personalization through ML, collaborate with teams, and ensure models align with user outcomes.

Develop machine learning models and optimize pricing algorithms to enhance Lyft's market dynamics, collaborating with cross-functional teams on real-world business problems.

As an Applied Scientist at Lyft, you will develop ML and optimization models for dynamic pricing, collaborate across teams, and implement algorithms to enhance rider experience.

The Director of Machine Learning Engineering is responsible for leading AI strategy, overseeing ML solutions, driving innovation, building teams, and ensuring operational excellence in ML systems.

Lead the development of production-grade machine learning systems, build ML pipelines, and optimize models for deployment and performance.

Lead the development of pricing algorithms for vehicle valuation at CarMax, managing a team of data scientists to implement strategies and maintain optimal pricing models.

This role involves building and optimizing ML systems and frameworks, collaborating with teams to enhance research and development in ML models.

As a Machine Learning Engineer, you'll design AI/ML solutions, optimize pipelines, integrate models, and enhance AI capabilities while collaborating with teams.

The Research Engineer/Scientist will advance decision-making in critical industries using optimization and machine learning, collaborating with product managers and engineers.

Lead a team of data scientists and ML engineers to build forecasting systems that drive data-driven decision-making for business metrics like revenue and user growth.

As a Software Engineering Intern, you'll develop features for user-facing products, work on API platforms, and design data pipelines while gaining hands-on experience in AI technologies.

The role involves developing ML models, conducting experiments, and optimizing car assignments to improve Waymo's Marketplace efficiency.

Design, build, and deploy AI features for claim synthesis; implement machine learning solutions and improve model performance through collaboration and evaluation.

Lead the development of AI-driven security workflows, integrate machine learning models, establish data pipelines, and mentor engineers.

Develop and operationalize machine learning models for lab automation, leveraging multimodal data and ensuring reliable predictive capabilities in drug discovery processes.

The role involves designing and implementing scalable ML-based solutions, analyzing data patterns, and producing reports while staying updated on AI advancements.

Develop machine learning and computer vision algorithms for automation and autonomy. Collaborate with experts, optimize solutions, and apply research insights.

Manage and grow the ML team, define goals and metrics, drive ML initiatives, build evaluation processes, and collaborate cross-functionally to enhance product delivery.