Senior/Staff FDE - Synthetic Data Generation

New York Cityfull timeOn Site

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senior

$180k–$320k

H1B: yes

Snorkel AI Senior/Staff Forward Deployed Engineer at Snorkel AI focused on Synthetic Data Generation to lead technical execution of customer engagements improving model training and evaluation. Responsible for designing scalable synthetic data pipelines and partnering with customers through full delivery lifecycle.

Responsibilities

Snorkel AI is hiring a Forward Deployed Engineer focused on Synthetic Data Generation to partner with leading AI labs and enterprises on their most critical AI initiatives.
Main Responsibilities
Synthetic Data Generation & Evaluation
Design and build scalable synthetic data generation, transformation, filtering, and evaluation pipelines for complex AI use cases
Translate model objectives, failure modes, and data gaps into synthetic data strategies, experiments, and technical specifications
Develop LLM- and ML-assisted workflows to generate high-quality training and evaluation datasets across targeted behaviors, domains, and edge cases
Build automated evaluators, quality checks, and measurement frameworks to assess correctness, relevance, diversity, coverage, and adherence to customer requirements
Design and run experiments to measure the impact of synthetic data on downstream model performance and iteratively improve generation approaches
Package and deliver production-grade datasets with standardized formats, quality assurance, and clear documentation
Forward Deployed Engineering & Customer Partnership
Lead technical workstreams from initial solution design through production delivery, navigating ambiguity and making sound technical decisions
Build, refine, and iterate on solutions that address customer needs, incorporating feedback to ensure the delivered work provides tangible value

Qualification

Experience building synthetic dataExperience working in fast-paced

Required

5+ years of experience in machine learning engineering, data science, applied AI, forward deployed engineering, or a similar technical role
Strong Python skills and experience building reliable production data or ML systems, including containerizing with Docker and deploying on cloud platforms (e.g., AWS, GCP, or Azure)
Hands-on experience with LLMs—building model-based applications and data workflows with the modern GenAI/LLM stack, and integrating systems, models, and data sources through APIs
Strong understanding of ML experimentation and evaluation, including defining metrics and using empirical results to guide technical decisions
Experience building synthetic data, data augmentation, or model-generated training and evaluation datasets
Experience with LLM evaluation techniques, including LLM-as-a-judge, model-based evaluation, rubric-based evaluation, or custom evaluators
Demonstrated ability to take ambiguous technical problems from problem definition through delivery, with strong technical communication and experience working directly with customers and cross-functional stakeholders
Experience serving as a technical lead—setting technical direction, driving architecture and key decisions, mentoring engineers, and creating reusable approaches that influence broader engineering or product outcomes

Preferred

Experience developing datasets for fine-tuning, preference optimization, or benchmarking, including human-in-the-loop generation and review workflows
Experience building agentic environments and tasks—repo-scale coding tasks, tool-agent-user interaction design, and agent tool protocols and interoperability
Experience with reinforcement learning for LLMs, including reward and verifier design and RL with verifiable rewards (RLVR)
Experience working in fast-paced, customer-facing environments where requirements and technical approaches evolve quickly

Benefits

Equity/RSU
Annual Bonus

Company

Snorkel AI

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Source: greenhouse

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Must-Have Skills for This Role

Synthetic Data GenerationLLMMLData PipelinesAPIs

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