Tech Lead Manager- MLRE, ML Systems

Scale's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework. Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation. Research and integrate state-of-the-art technologies to optimize our ML system. Ideally you’d have: Passionate about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc. Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills to operate in a cross functional team environment. Nice to haves: Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale AI for eligible roles include base salary, equity, and benefits. The base salary range displayed reflects the minimum and maximum target for new hire salaries for the position, determined by work location and factors including job-related skills, experience, interview performance, and education or training. Eligible employees are granted equity-based compensation, subject to Board approval. The recruiter can share the specific salary range for your location during the hiring process and confirm equity eligibility. Benefits include health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. This role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for location. For pay transparency, the base salary range for this full-time position in San Francisco, New York, and Seattle is: $275,000 - $350,000 USD. Our policy requires a 90-day waiting period before reconsidering candidates for the same role to ensure a fair and thorough evaluation of all applicants. About Us: Scale AI’s mission is to develop reliable AI systems for the world's most important decisions. We provide high-quality data and full-stack technologies powering leading models and AI applications for enterprises and governments. We are an inclusive and equal opportunity workplace and do not discriminate on the basis of protected characteristics. We are committed to reasonable accommodations in the application process for applicants with disabilities. For accommodations, please contact us at View email address on click.appcast.io. We also share information about our privacy practices regarding applicant data in our privacy policy. Voluntary Self-Identification of Disability is optional and confidential. Providing this information is voluntary and will not affect your application. This information is used to measure the effectiveness of workforce diversity efforts and is kept confidential. Information collected is in accordance with applicable laws and internal policies. #J-18808-Ljbffr Scale AI