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Machine Learning Research Developer - Model Training & Training
Leading AI Lab
We are partnering with a mission-driven AI research organization seeking a Machine Learning Research Developer to support a cutting-edge research agenda focused on advanced AI systems. This role sits at the intersection of research and engineering, working closely with ML scientists to address complex training and inference challenges involving very large-scale models.
Key Responsibilities
- Partner with ML researchers to accelerate experimentation, large-scale model training, and inference workflows
- Implement and optimize novel model architectures and simulated research environments
- Design and maintain robust experimental workflows across exploratory prototypes and production-scale research initiatives
- Build internal tools and libraries to maximize computational efficiency and resource utilization
- Establish and document best practices for model development, reproducibility, and infrastructure reliability
Skills & Qualifications
- Bachelor’s/Master's degree in Computer Science, Computer Engineering, Software Engineering, or a related technical field required. PhD welcomed not required.
- Advanced degree (MSc or higher) in Machine Learning, AI, or equivalent practical experience
- 3+ years of industry experience designing and deploying complex ML workflows on high-performance compute infrastructure
- Strong proficiency with modern ML frameworks such as PyTorch, TensorFlow, or JAX
- Experience working with cloud platforms (AWS, GCP, or Azure)
- Familiarity with containerization and orchestration tools (Docker, Kubernetes)
- Experience working with data infrastructure and modern data platforms (e.g., vector databases)
- Demonstrated contributions to high-quality deep learning research initiatives
- Ability to collaborate cross-functionally and document engineering standards clearly
What’s Offered
- Opportunity to contribute to a high-impact research mission in advanced AI
- Comprehensive health benefits
- Competitive paid time off
- Employer retirement contribution
- Flexible benefits supporting overall well-being
- Collaborative, research-driven environment with experienced technical peers
- Modern, centrally located office environment with convenient transit access
Sprachkenntnisse
- English
Hinweis für Nutzer
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