Top Machine Learning Engineer Jobs

Develop deep learning models for autonomy applications, implement ML algorithms for self-driving vehicles, and resolve real-world testing issues.

Join PatternAI's data team as a Machine Learning Engineer, building ML pipelines and managing MLOps infrastructure for model optimization.

The Machine Learning Engineer will develop and manage production ML systems for renewable energy deals, focusing on user feedback and model performance.

Develop and deploy models for the Piai claims-intelligence platform using machine learning, NLP techniques, and collaboration with various teams.

Lead high-impact AI/ML projects in the automotive domain, overseeing technical strategy, project execution, and client management, while mentoring junior team members.

The role involves leading machine learning initiatives to enhance automated testing for autonomous vehicles, improve model interpretability, and collaborate with cross-functional teams.

As an AI/ML Engineer, you will design and deploy models for real-world applications, optimize data pipelines, and engage with global leaders to enhance AI technology's impact across sectors like healthcare and government.

As an Open-Source Machine Learning Engineer, you'll improve the ML ecosystem using existing libraries and engage with the community, enhancing accessibility to AI tools.

As a Machine Learning Engineer at Verneek, you'll develop AI/NLP models, tackle complex AI research problems, and innovate within an early-stage deep-tech startup environment.

Develop technologies for optimizing AI models in autonomous driving. Collaborate on parallel algorithms and influence compute platform architecture.

As a Machine Learning Engineer, you will focus on user-behavioral modeling, collaborate with teams, and engage in data processing and model deployment.

As a Machine Learning Engineer at Yobi, you will design and optimize systems for real-time model serving and inference, ensuring performance and reliability.

The Staff Machine Learning Engineer will lead the development of ML systems targeting user growth and monetization, optimizing user experiences, and improving engagement.

As the AI/ML Developer Evangelist, you'll advocate for Encord, create technical content, and engage within developer communities to enhance product adoption.

Design and implement reinforcement learning algorithms for robotics, conduct experiments, optimize models, and collaborate with cross-functional teams.

Design, build, and deploy machine learning solutions. Collaborate with teams to transform research into practical applications using large datasets.

This role involves architecting scalable AI inference solutions, leading a team, and optimizing distributed systems using machine learning and cloud infrastructure.

The Machine Learning Engineer will design, train, deploy, and maintain ML systems for automation, forecasting, and analytics in music and entertainment. Responsibilities include ML model development, MLOps tooling, and collaboration with other teams.

Contribute to AI Inference projects by designing and developing distributed systems for scalable LLM deployments, focusing on Kubernetes and inference optimization.

Lead the end-to-end machine learning lifecycle for AI products, managing data pipelines and model development to optimize performance and accuracy in production.

Join the AI Engineering team at Nightfall to design, enhance, and deploy AI systems for data security using Python and Go, focusing on NLP and LLMs.

The Machine Learning Engineer will design, deploy, and maintain ML models, work with large datasets, and collaborate with teams to enhance AI solutions.

The Staff Machine Learning Engineer will design, code, and deploy ML models, improve backend systems, and mentor engineers.

As a Machine Learning Engineer at Hive, you will prototype, train, and deploy deep learning models, analyze results, and collaborate with cross-functional teams to implement machine learning solutions in production.

The Staff Machine Learning Engineer will implement ML models, design neural networks, maintain scalable code, and lead cross-functional collaborations in AI development.