Research Engineer, Harmonic

• BS in Computer Science, related technical fields, or equivalent industry experience
• 2+ years of experience focused on training large language models
• Knowledge of cutting-edge models, and experience building evaluations for model capability
• Expertise in Python and PyTorch
• Experience with distributed training, parallel computing, and GPU acceleration
• Strong experience with large-scale GPU clusters, HPC environments, and job scheduling/orchestration tools (e.g., SLURM or Kubernetes)

Desirable

• We are seeking a highly motivated and skilled Research Engineer with expertise in model training, to focus on reasoning in formal and informal settings
• The successful candidate will play a key role in scaling our reinforcement learning systems beyond human-level capabilities
• Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimization
• Optimize and scale our training infrastructure to improve efficiency and reliability in a reinforcement learning setting