Senior Research Engineer, LLM Training & Post-Training (PyTorch)

Location: Hybrid with a minimum of 2 in-office days per week in San Francisco, Seattle, New York City, or London; fully remote work is considered for candidates outside the office hub locations.

Annual base salary: $165,000–$310,000 USD, plus discretionary bonus, equity, and benefits.

Company

hirify.global builds an end-to-end platform for developing, training, and deploying AI systems, combining developer-first software with large-scale AI compute.

What you will do

• Design, build, and optimize training and post-training pipelines for large language models.
• Improve model quality through continued pretraining, supervised fine-tuning, preference optimization, reinforcement learning, reward modeling, evaluation, and experimentation.
• Build PyTorch-based training infrastructure, research tooling, and developer workflows.
• Optimize distributed multi-GPU training for throughput, memory efficiency, scalability, and GPU utilization.
• Investigate convergence, instability, communication overhead, and performance bottlenecks; design benchmarks and analyze model failure modes.
• Collaborate with research, infrastructure, platform engineering, and customers to develop production-ready AI systems and open-source improvements.

Requirements

• Significant experience training, fine-tuning, evaluating, and optimizing transformer-based language models with PyTorch.
• Experience with modern LLM training and post-training methods, including SFT, RLHF, DPO, PPO, GRPO, reward modeling, or similar approaches.
• Strong understanding of distributed training and multi-GPU systems, including performance, scalability, or efficiency optimization.
• Strong software engineering fundamentals and experience building production-quality Python software and research tooling.
• Experience designing experiments, evaluating model performance, and debugging complex training or optimization issues.
• Master’s degree, PhD, or equivalent industry experience in Machine Learning, AI, Computer Science, or a related field.

Nice to have

• Experience with DeepSpeed, FSDP, Megatron-LM, Hugging Face Transformers, TRL, PEFT, Lightning Fabric, or similar frameworks.
• Experience with CUDA, Triton, vLLM, SGLang, TensorRT, GPU optimization, mixed precision, or memory optimization.
• Open-source contributions, research publications, production AI platform experience, or startup experience.

Culture & Benefits

• Hybrid work model for office-based teams, flexible schedules, and occasional company and team offsites.
• Medical, dental, and vision coverage, meaningful equity, and retirement contributions, including 401(k) matching in the U.S. and pension contributions in the U.K.
• Unlimited PTO, company holidays, floating holidays, and a two-week company-wide winter break.
• Paid parental and family leave, wellness and work-from-home stipends, and an annual learning and development allowance.
• Four weeks of paid sabbatical leave after four years and complimentary meals at office hubs.