Senior Machine Learning Engineer

What you'll do

• Train, fine-tune, and distill production models; develop adversarial training and data pipelines.
• Build low-latency model-serving infrastructure and online/offline evaluation systems.
• Diagnose model failures and collaborate across teams to translate customer governance needs into model improvements.

What they ask for

• 2+ years of professional ML experience with end-to-end production model ownership.
• Proficiency in Python and PyTorch (or equivalent), plus production experience training, fine-tuning, or distilling language models or classifiers, including SFT and at least one preference-optimization technique.
• Production experience with serving frameworks such as vLLM, SGLang, or TensorRT-LLM (or equivalent), including inference optimization.
• Experience building closed-loop ML systems and operating models at production scale in safety-critical request paths.

Nice to have

• Background in AI safety and red-teaming, or expertise in LLM-as-judge evaluation and calibration.
• Experience with retrieval or context-fusion systems, low-latency inference, data mining, distillation, or agentic ecosystems.

Pay

$188,500–$282,700 USD (base salary)

Tools

Python, PyTorch, vLLM, SGLang, TensorRT-LLM, DPO, RLAIF, RLHF

AI focus

Develop specialized small language models and classifiers for real-time AI-agent governance, safety enforcement, anomaly detection, and remediation; improve them through training, evaluation, and production feedback.