Senior/Staff FDE - Synthetic Data Generation

What you'll do

• Build and evaluate scalable synthetic-data generation pipelines, evaluators, and quality frameworks; measure effects on downstream model performance.
• Lead customer technical workstreams from discovery and design through implementation and delivery, communicating results and resolving blockers.
• Turn successful engagement solutions into reusable pipelines, tools, standards, and product improvements; guide other engineers.

What they ask for

• 5+ years in machine learning engineering, data science, applied AI, forward deployed engineering, or a similar technical role.
• Strong Python skills; production data or ML systems experience, including Docker and cloud deployment (AWS, GCP, or Azure).
• Hands-on LLM application and data-workflow experience, including API integration; strong ML experimentation and evaluation skills.
• Experience with synthetic data or data augmentation, LLM evaluation, customer-facing delivery of ambiguous problems, and technical leadership.

Nice to have

• Datasets for fine-tuning, preference optimization, or benchmarking, including human-in-the-loop workflows; agentic environments and tasks.
• Reinforcement learning for LLMs, including reward and verifier design and RLVR; experience in fast-paced customer-facing environments.

Pay

$180,000–$320,000 USD base salary

Tools

Python, Docker, AWS, GCP, Azure, LLMs, APIs

AI focus

Develop synthetic data generation and evaluation workflows—including LLM- and ML-assisted dataset creation—to improve model training, evaluation, and performance.