Top Machine Learning Jobs

As a Lead Machine Learning Engineer, you'll design and scale ML infrastructure, collaborate across teams, and mentor engineers in AI and ML innovations.

The role involves designing and building ML models, managing teams, optimizing ML systems, and implementing cloud-based architectures. Collaboration with product and data science teams is crucial.

Support Acute Care Informatics by developing ML/AI solutions; collaborate with clinicians to enhance clinical data analytics through algorithms and cloud technologies.

Lead a local AI/ML team, drive AI innovations, mentor team members, and manage projects within the ML development lifecycle using Agile methodology.

Design and develop geometry processing, simulation algorithms, and data services for engineering applications while optimizing machine learning workflows and managing datasets.

Develop machine learning features for autonomous vehicles, evaluate ML methods, and lead experiments while collaborating with multi-functional teams.

As a Machine Learning Intern, you will lead projects, analyze data, build models, and solve complex problems using machine learning and AI techniques.

The Machine Learning Engineer will develop and improve ML models for product surfaces, build data processing pipelines, and leverage machine learning technologies in advertisements.

The Senior Machine Learning Engineer will design, prototype, build AI systems, evaluate ML models, and improve Vectara's AI Agents with a focus on reliability and performance.

The Staff Machine Learning Engineer will design ML systems, mentor engineers, work on AI product development, and improve legal data processing.

The Senior Machine Learning Engineer will design and implement ML systems, optimize data pipelines, and collaborate on ML workflows for personal injury legal solutions.

Lead the development of machine learning solutions for video personalization, enhancing user experience through data-driven insights and collaboration across teams. Drive technical strategy in building scalable systems and partnerships to innovate customer recommendations.

Lead a team of applied data scientists and ML engineers to develop scalable forecasting systems. Collaborate cross-functionally to integrate forecasting insights into decision-making processes and business strategies.

The role involves building machine learning algorithms, implementing data cleaning processes, and developing predictive models in the energy sector.

Design and scale systems for personalization and ranking using ML. Mentor engineers and lead initiatives in a consumer-focused environment, leveraging AI tools.

The Sr. Machine Learning Engineer at Zscaler will build and implement AI features, design resilient microservices, and ensure operational excellence in digital experiences.

Lead the AI/ML initiatives at Legion, develop forecasting models, manage a team of ML specialists, and engage with clients on tech adoption.

Research Engineer will conduct Machine Learning research to enhance localization and global entertainment, focusing on ASR, Speaker Diarization, and Audio Understanding.

Design and implement scalable machine learning pipelines, mentor junior team members, ensure deployment standards, build CI/CD pipelines, and establish best practices for ML systems.

Lead the architectural design of data and machine learning systems for a global creator marketplace, focusing on recommendations, data ingestion, and real-time optimization.

The candidate will develop algorithms for optimizing therapeutic mRNAs, collaborate with teams on data acquisition, and communicate findings. A Ph.D. in a relevant field is required along with experience in machine learning and bioinformatics.

The Staff ML Engineer will design and implement backend components for the ML Inference Platform, ensuring efficient model serving and collaborating with ML teams to enhance AI infrastructure at GM.

The AI/ML Engineer will design, build, and deploy machine learning systems, optimize workloads, and ensure scalability and compliance of the ITMS platform.

The role involves developing AI and Machine Learning solutions to enhance enterprise services, collaborating with cross-functional teams, and ensuring high-quality deliverables.

The role involves developing an AI agent platform, building ML models, and enhancing user experiences with advanced algorithms. Collaboration and fast-paced execution are key.