The company is looking to design and optimize large-scale AI models that drive real-world innovation across industries.
Requirements
- Strong programming experience in at least one core language (e.g., Python, C++, or Java).
- Proven hands-on experience with deep learning and machine learning, including training, fine-tuning, and deploying models.
- Expertise in developing or optimizing generative AI models and frameworks.
- Proficiency with machine learning libraries such as PyTorch or TensorFlow.
- Familiarity with the full software development lifecycle, including code reviews, CI/CD pipelines, and testing.
Responsibilities
- Customize state-of-the-art large language models for various domains, languages, and modalities using techniques like continued pre-training, fine-tuning, and Reinforcement Learning with Human Feedback (RLHF).
- Build and maintain high-performance, distributed training pipelines for large-scale LLMs using tools like DeepSpeed and Fully Sharded Data Parallel (FSDP).
- Optimize AI models for AWS's custom silicon (Inferentia and Trainium) using the AWS Neuron SDK and low-level performance enhancements.
- Work closely with enterprise customers and foundational model partners to understand challenges and co-develop AI solutions that align with their business needs.
Other
- 10+ years of professional experience in software development, including experience with system architecture, design, and leadership.
- Masters Degree/Ph.D. preferred in Computer Science or a related technical field.
- 2+ years of experience in deploying or optimizing machine learning models in production environments.
