Senior Machine Learning Engineer

📋 Description

• End-to-end ML lifecycle: data curation, training, and production serving.
• Real-time policy enforcement models with Agent Rewind.
• Improve accuracy, latency, and cost for governance tasks.
• Build high performance inference infra for real-time and batch workloads.
• Develop synthetic data pipelines and online/offline evaluation.

🎯 Requirements

• 2+ years of professional ML experience with end-to-end production ownership.
• Proficiency in Python and PyTorch for production-grade training.
• Hands-on LM training, fine-tuning, or distillation; includes SFT and DPO/RLAIF/RLHF.
• Production serving experience with frameworks (vLLM, TensorRT-LLM) and optimizations.
• Experience designing closed-loop ML systems with eval, telemetry, and data curation.
• Comfort operating at production scale with high QPS in safety-critical paths.
• Bachelor's degree in CS, ML, CE, or related field.

🎁 Benefits

• Collaborative team shipping models to enterprise customers.
• Strong focus on AI safety and governance.
• Inclusive culture with equal opportunity and support.