Top Machine Learning Jobs

As a Machine Learning Engineer Intern, you'll tackle challenges in ML including training models, optimizing inference on GPU, and documenting findings.

As a Machine Learning Intern, you'll develop models, manage projects end-to-end, and collaborate with customers to improve AI solutions.

As a Machine Learning Engineer at Captions, you will optimize and deploy large multimodal video diffusion models, building high-performance inference pipelines and ensuring low-latency predictions at scale.

The Staff AI & ML Engineer at AlixPartners will design, implement, and deliver AI/ML solutions while leading teams and driving innovation across products.

Design and develop scalable machine learning systems for fraud insights, collaborating with teams to deliver high-quality ML infrastructure effectively.

The internship involves applying AI and ML to Nike's data, developing innovative solutions, participating in real business initiatives, and collaborating with teams.

Develop and deploy machine learning models for lead scoring, implement NLP systems, and optimize model performance while collaborating with the backend team.

Develop and deploy machine learning systems, engage in the design and training of models, collaborate across teams, and learn new technologies.

As a PhD Machine Learning Engineer Intern, you'll develop and deploy machine learning systems, collaborate across teams, and enhance Stripe's financial products.

The Lead Machine Learning Engineer will develop, optimize, and deploy machine learning models while collaborating on AI-capable solutions for edge and cloud applications.

Lead and develop a team of ML engineers and data scientists, guiding the creation of ML solutions with advanced techniques in AI, focusing on user-friendly systems.

The Senior Machine Learning Engineer will enhance HP's retrieval systems and recommendation algorithms, focusing on AI-driven user interactions and system performance improvements.

The Machine Learning Scientist will design experiments, analyze AI model behaviors, and develop metrics to improve model evaluation, collaborating closely with engineers and product teams.

The Machine Learning Engineer II will optimize ML model execution on GPU platforms, develop App Engine SDK features, and ensure code quality.

Design and implement advanced software for GPU-based machine learning applications in autonomous driving, optimizing resource usage, and collaborating on feature integrations.

Design and implement scalable ML systems, optimize models for production, and collaborate with teams to develop AI applications.

As a Principal ML Engineer, you will design ML architecture, tackle technical challenges, mentor engineers, and influence ML strategy across the company.

Lead a team of Machine Learning Research Scientists to advance deep learning and LLM integration in adtech solutions. Responsibilities include overseeing model design, enhancing algorithms, mentoring staff, and maintaining active participation in the development process.

Lead the development of machine learning models for lending products, manage a data science team, and ensure compliance with regulations.

The Staff Machine Learning Engineer will lead the development of AI systems for Unity, focusing on multi-agent systems, reinforcement learning, and AI planning for games and simulations.

The ML Engineer will build, deploy, and iterate on ML systems, focusing on classification, human feedback loops, and working with real-world data.

You will explore and develop machine learning solutions for autonomous driving, collaborating with various teams to enhance technology.

Develop and implement machine learning models for evaluating disputes and chargebacks, and create a model orchestration layer. Collaborate on data use for enhanced user experiences.

The Sr. Staff Machine Learning Engineer will lead architecture and development of ML systems, enhance patient interactions, optimize treatment recommendations, and mentor engineers.

The Machine Learning Engineer will prototype and evaluate LLM features, collaborate with teams, contribute to technical design, and measure success metrics.