ReflectionAI
Member of Technical Staff - Pre-Training Infra
San Francisco · Staff+
H1B sponsorship availableDetected 119 days ago
Machine LearningA/B TestingResearchCommunication
About the role
- Improve performance of distributed training workloads through optimization of communication, memory usage, and GPU utilization.
- Debug and resolve performance bottlenecks across distributed training stacks including model parallelism, GPU communication, and training runtime systems.
- Contribute to the development of systems that enable rapid experimentation and iteration on new training techniques.
Responsibilities
- Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on.
- We build open models that let anyone control their intelligence and help shape the future of AI.
- Build and scale distributed training systems that power frontier model pre-training.
- Work closely with research teams to design and operate large-scale training runs for foundation models.
- Collaborate directly with pre-training researchers to translate experimental ideas into scalable, production-ready training systems.
- Build and maintain training pipelines that support large-scale datasets, checkpointing, and experiment iteration.
- Sponsorship support: We sponsor visas to help exceptional talent join our team and support long-term immigration pathways where applicable.
- Team building: We have regular off-sites, happy hours, and team celebrations.
- Joining Reflection means building from the ground up as part of a talent-dense team.
Requirements
- Familiarity with large-scale model parallelism strategies (data, tensor, pipeline, or expert parallelism).
- Experience optimizing training throughput and GPU utilization in large distributed environments.
- Familiarity with GPU communication libraries such as NCCL and performance tuning for distributed workloads.
- Experience working closely with ML researchers to productionize experimental training workflows.
- Experience working with large datasets and training pipelines used for foundation model pre-training.
Skills
- Strong experience working with modern distributed training frameworks such as Megatron, DeepSpeed, or similar large-scale training systems.
- Strong debugging skills across GPU compute, distributed training systems, and large-scale ML pipelines
Compensation
- Salary and equity structured to recognize and retain our talent globally.
- Health & wellness: Comprehensive medical, dental, vision, and life, with an annual wellness allowance.
Benefits
- Top-tier compensation: Salary and equity structured to recognize and retain our talent globally.
- Stock options: Everyone who joins and contributes to Reflection's success gets to share in the upside through stock options.
- Health & wellness: Comprehensive medical, dental, vision, and life, with an annual wellness allowance.
- Life & family: 22 weeks paid parental leave for all new birthing and non-birthing parents, including adoptive and surrogate journeys.
- Vacation days: Unlimited paid time off in the U.S. and 30 days in the U.K.
Company info
- make intelligence open and accessible to all.
Visa & Work Authorization
- We sponsor visas to help exceptional talent join our team and support long-term immigration pathways where applicable.
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This listing is sourced directly from ReflectionAI's careers page and normalized into a canonical job model.