Senior AI & ML Engineer — Remote-friendly, Synthetic Environments

Cacheflow; San Francisco (CA); Hybrid; USD 180,000 - 260,000; Full time

Benefits offered by this job

Competitive salary and equity

Unlimited paid time off

401k plan with employer contribution

Medical, dental, and vision insurance

Generous parental leave policy

Remote-friendly work environment

Job summary

Tonic builds the data infrastructure behind modern AI. The models you build here are load-bearing, impacting whether agents are ready to ship and how realistic synthetic environments are.

You’ll work on synthesis and de-identification models with real enterprise data and high-stakes challenges that defy textbook answers. You’ll design scalable systems for synthetic environments, train and evaluate models at scale, and collaborate with frontier labs and enterprise ML teams to drive concrete model

Qualifications

• 8+ years (or PhD with 3+ years) building production ML systems.
• Experience with LLMs, agents, RL, NER, or information extraction.
• Hands-on experience training and shipping models to production.
• Fluency with modern training/eval stacks (PyTorch, distributed training).

Responsibilities

• Design and build the systems that generate longitudinally coherent synthetic environments for agent training and evaluation.
• Build synthesis models that generate realistic replacement values at large scale, preserving format and distribution.
• Train and improve the NER models behind entity detection across free text and structured data.
• Build evaluation infrastructure that grades agent outcomes on real tasks.
• Fine-tune open-weight models on Tonic-generated data and turn results into direction.
• Expand coverage into new domains, languages, and entity types.
• Own model evaluation across precision/recall and outcome-level grading.
• Optimize inference for large volumes of sensitive data inside customer environments.
• Partner with frontier labs and enterprise ML teams to ship model improvements.
• Set technical direction for a small, senior team.

Skills

LLMs

Agents

Reinforcement Learning

NER

Information extraction

Education

PhD inCS/ML

Tools

PyTorch

Distributed training

Benchmark frameworks

Job description

Tonic builds the data infrastructure behind modern AI. The models you build here are load-bearing, impacting whether agents are ready to ship and how realistic synthetic environments are.

You’ll work on synthesis and de-identification models with real enterprise data and high-stakes challenges that defy textbook answers. You’ll design scalable systems for synthetic environments, train and evaluate models at scale, and collaborate with frontier labs and enterprise ML teams to drive concrete model