Job Description
The client is a venture-backed startup focused on transforming how enterprises deploy and scale AI systems. Their platform simplifies and accelerates the deployment of customized, safe, and aligned AI solutionsgoing from concept to fully operational applications in days instead of months.
Their core innovation includes proprietary alignment technology, leveraging cutting-edge research in reinforcement learning and AI safety. The client specializes in creating powerful AI evaluation systems tailored specifically to the brand values and strategic goals of leading global enterprises.
Backed by top-tier investors, they are dedicated to building the future of safe, robust, and highly effective AI solutions.
Join the client and be part of redefining what's achievable with AI!
Requirements
- PhD or Master's degree in Computer Science, Machine Learning, or a related technical discipline.
- 3+ years of experience in industry ML research roles or equivalent academic research experience.
- Deep expertise in ML systems, particularly distributed training of large-scale models or optimization of ML systems for performance.
- Strong understanding of LLMs, their architectures, and their practical applications.
- Hands-on experience with fine tuning open source LLMs.
- A history of meaningful contributions to research communitiesopen-source projects or publications in top-tier conferences (NeurIPS, CVPR, ICCV/ECCV, etc.).
- Solid software engineering fundamentals combined with proven empirical research skills.
- Excellent teamwork, communication, and presentation capabilities.
Qualification
Master's Degree
Key skill Required
- Academic Research
- Communication
- Computer Science
- Discipline
- Empirical Research
- Fine Tuning
- Focused
- History
- Innovation
- Learning
- Machine Learning
- Optimization
- Practical
- Presentation
- Publications
- Reinforcement
- Reinforcement Learning
- Research
- Research Skills
- Science
- Software Engineering
- Teamwork
- Training
