Дополнительно
The product and sales teams have a library of working, polished demos they reach for on calls
Enterprise customers you've touched have meaningfully faster time-to-value than those you haven't
At least 2–3 product changes were shipped because of feedback you originated
The team understands where applied AI is heading 6–12 months from now, partly because you told them
You've fine-tuned large models, debugged distributed training jobs, built production RAG or agentic pipelines, and optimized inference on GPU infrastructure — not just read about it
You're fluent in the modern ML stack: PyTorch, HuggingFace, CUDA fundamentals, Kubernetes for ML, MLflow or equivalent, vector databases
You've worked with enterprise ML teams — whether as a solutions engineer, customer engineer, or an ML engineer who collaborated closely with customers
You read papers and implement them — not for credit, but because it's how you stay sharp
You communicate with calibration: you can explain activation checkpointing tradeoffs to an ML engineer in the morning and the cost implication to a CTO in the afternoon
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Pay Transparency
Base Compensation Range
$200—$350,000 USD