Top Machine Learning Jobs

As a Machine Learning Engineer at Onyx, you will enhance agent and knowledge retrieval capabilities by implementing LLM-based graphs and advanced NLP algorithms, while collaborating with the team to improve user experience and product direction.

Develop algorithms in machine learning and statistics to address complex challenges. Design data pipelines and deploy solutions using cloud infrastructure.

The Machine Learning Engineer will build data pipelines, manage multi-GPU training infrastructure, optimize code, and deploy inference pipelines for LLMs.

The AI/ML Developer II develops machine learning models, collaborates with teams, and automates infrastructure while ensuring quality and reliability in software solutions.

As a Staff Machine Learning Engineer, you will develop machine learning models and optimization algorithms for Coupang's advertising platform, focusing on improving ad targeting and engagement.

The Senior Machine Learning Engineer will lead applied research projects, design and implement ML models, maintain data pipelines, and mentor junior members for defense-focused missions.

Responsible for designing, building, deploying, and maintaining production-grade AI and ML solutions in a cloud-native environment, while collaborating with engineering and data teams.

The AI/ML Engineer will design and implement AI solutions, collaborating with various teams to enhance production-grade services using ML and MLOps practices. Responsibilities include model lifecycle management, security measures, and ensuring reliability in AI applications.

Lead design, development, and production deployment of ML and algorithmic solutions. Own end-to-end ML systems, support distributed production reliability, communicate tradeoffs, and apply generative AI, LLM fine-tuning, RAG, and agentic techniques to product problems.

The Senior Machine Learning Engineer will design, train, and evaluate ML models to solve complex problems, mentor others, and optimize production systems.

Responsibilities include designing workflows, optimizing algorithms, developing Machine Learning solutions for EDA, and collaborating with cross-functional teams.

The Principal ML/AI Engineer will shape the AI vision, prototype AI systems, and architect an AI-ready technical stack while mentoring teams and collaborating with executives.

As a Lead Machine Learning Engineer, you will develop and implement ML models, optimize data pipelines, and collaborate with cross-functional teams to enhance business solutions.

The Applied Machine Learning Scientist will develop insitro's ChemML platform and integrate AI for drug discovery, collaborating cross-functionally.

As a Principal Machine Learning Engineer, you will architect AI solutions, collaborate with scientists, and optimize models for edge deployment. Your work enhances public safety applications.

This position involves designing algorithms, analyzing user data, optimizing workflows, and collaborating with cross-functional teams to enhance grocery product discovery and personalization at Uber.

Design and build machine learning algorithms to optimize e-commerce search and improve overall platform matching capabilities, supporting TikTok's rapid e-commerce development.

The Machine Learning Engineer will apply data science and machine learning practices to solve problems, develop prototypes, and communicate insights to stakeholders in a dynamic environment.

The ML Engineer will architect and build personalization and recommendation systems, design user preference algorithms, collaborate with teams, and improve systems from research to production.

As a Senior Machine Learning Engineer, you'll design and implement large-scale E2E driving models, enhance data workflows, and collaborate with cross-functional teams to advance autonomous driving technologies.

The Machine Learning Engineer II will enhance ML capabilities for autonomous vehicles, train and optimize models, and ensure high performance through collaboration with cross-functional teams.

The Senior Machine Learning Engineer will design, develop, and deploy production ML models, owning the entire ML lifecycle and collaborating with various teams to enhance product experiences and decision-making systems.

The ML Engineer will develop and advance multimodal models for robot perception and behavior, integrating these systems into hardware while collaborating closely with robotics engineers.

As an intern, you'll develop software and machine learning systems for robots, focusing on perception, intelligence, behavior, and real-time software integration.

Contribute to ML system design, development, and evaluation for recommendations, collaborating to integrate and A/B test signals, promoting best practices.