Senior GenAI Research Engineer - Optimization and Kernels

Job Description As a Sr. Research Engineer on the Scaling team, you will be responsible for keeping up with the latest developments in deep learning and advancing the scientific frontier by creating new techniques that go beyond the state of the art. You will work together on a collaborative team of researchers and engineers with diverse backgrounds and technical training. And most importantly, you will love our customers: our goal is to make our customers successful in applying state‑of‑the‑art LLMs and AI systems, and we encode our scientific expertise into our products to make that possible. Impact you will have As a research engineer on the Scaling Team at the company, you will: Drive performance improvements through advanced optimization techniques including kernel fusion, mixed precision, memory layout optimization, tiling strategies, and tensorization for training‑specific patterns Design, implement, and optimize high‑performance GPU kernels for training workloads (e.g., attention mechanisms, custom layers, gradient computation, activation functions) targeting NVIDIA architectures Design and implement distributed training frameworks for large language models, including parallelism strategies (data, tensor, pipeline, ZeRO‑based) and optimized communication patterns for gradient synchronization and collective operations Profile, debug, and optimize end‑to‑end training workflows to identify and resolve performance bottlenecks, applying memory optimization techniques like activation checkpointing, gradient sharding, and mixed‑precision training. What We Look for BS/MS/PhD in Computer Science or related field with hands‑on experience writing and tuning CUDA kernels for ML training applications, or hands‑on experience in distributed training frameworks (PyTorch DDP, DeepSpeed, Megatron‑LM, FSDP) Strong understanding of NVIDIA GPU architecture (memory hierarchy, tensor cores, warp scheduling, SM occupancy) and proficiency with CUDA debugging/profiling tools (Nsight, NVProf) Deep understanding of parallelism techniques and memory optimization strategies for large‑scale model training, with proven ability to debug and optimize distributed workloads Strong software engineering skills in Python and PyTorch, with experience supporting production training workflows and knowledge of LLM training dynamics including hyperparameter tuning and optimization strategies. Pay Range Transparency The company is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non‑commissionable roles or on‑target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job‑related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, the company anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

$166,000 — $225,000 USD

Benefits At the company, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please consult your local benefits information. Our Commitment to Diversity and Inclusion At the company, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at the company are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio‑economic status, veteran status, and other protected characteristics. Compliance If access to export‑controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone. #J-18808-Ljbffr United States Digital Space LLC