Top Machine Learning Engineer Jobs

The role involves building and scaling infrastructure for machine learning, particularly focused on Large Language Models, while providing technical leadership and mentoring juniors.

As a Senior Machine Learning Engineer, you will design and implement ML systems for conversational AI and intelligent automation, collaborating with cross-functional teams and mentoring colleagues.

The role involves developing large-scale data processing pipelines, automating data selection, and collaborating on ML model improvements to enhance vehicle performance and safety.

Design, develop, and implement machine learning models and algorithms to solve complex problems, collaborating with data scientists and software engineers.

Develop algorithms and optimizations for inference and compiler stack, enhance performance metrics, collaborate with hardware teams, and publish work on novel approaches.

The Senior Machine Learning Engineer will design multimodal models, optimize ML deployment for real-time inference, and mentor junior engineers.

Design and implement teacher-student model frameworks, optimize models for real-time deployment, and mentor engineers while engaging in reinforcement learning applications.

As a Senior Machine Learning Engineer, you'll build teacher-student models, implement reinforcement learning, and optimize deployments for autonomous driving applications while mentoring junior engineers.

Design and implement teacher-student ML models for multimodal sensor data, optimize deployment for real-time inference, and mentor engineers.

The Process Engineer IV will design and optimize manufacturing processes, leverage AI/ML for data analysis, and mentor less experienced engineers.

The Senior Engineer in AI & ML will design and productionalize machine learning models, collaborating with Data Scientists to implement scalable solutions and enhance customer experiences at CarMax.

The Software Engineer II will design, develop, and maintain APIs and microservices, collaborate across teams, and enhance engineering workflows using AI/ML.

Assist in migrating medical imaging AI algorithms from C++ to Python and from CPU to GPU compute, while gaining exposure to cardiac AI technologies and cloud architectures.

Lead architectural design of AI/ML solutions, mentor staff, and ensure data governance compliance in high-scale enterprise environments.

As a Senior Machine Learning Engineer, you'll develop advanced AI systems, focusing on search ranking, recommendation engines, and document extraction. You'll oversee model design, implementation, and deployment while collaborating with teams to innovate construction technology solutions.

Lead the development of AI/ML infrastructure for simulations. Collaborate on realism models, scale distributed systems, and ensure alignment with business goals.

The Staff Machine Learning Engineer will design, develop, and optimize machine learning applications, mentor junior engineers, and conduct research to enhance Quantcast's ML systems.

As an AI/ML Platform Engineer, you'll design and manage ML pipelines on Azure, operationalize AI solutions, and automate deployment processes while collaborating with diverse technical teams.

The Senior Machine Learning Engineer will enhance recommendation systems, employ AI/LLM technologies, and drive AI innovation for content discovery and user engagement.

The role involves applied research on market data to create predictive trading signals, designing features for strategies, and collaborating with teams for execution.

Build and optimize the ML infrastructure for Coupang Ads Tech, improving the lifecycle of ML engineering for enhanced developer experience and efficiency.

The ML Infrastructure Engineer will develop and scale AI safety systems infrastructure, optimize machine learning pipelines, and ensure reliable system performance while collaborating with research teams.

The role involves developing and deploying NLP models, specifically focusing on LLMs. Responsibilities include designing models, implementing MLOps practices, and collaborating with teams to enhance webAI's platform.

Design and implement MLOps systems for ML and LLM services, ensure reliability, and collaborate across teams to optimize AI solutions.

Lead a multi-disciplinary team to drive software evolution for machine learning accelerators, collaborating closely with hardware teams and managing virtual relationships.