Applied AI Research Engineer
Netic - San Francisco, California, United States
Posted May 30, 2025
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- 401(k) match
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Schedule
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- Weekend work
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Application
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Where they hire
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About this role
Applied AI Research Engineer San Francisco, California, United States Netic is the AI revenue engine for essential services who are the backbone of the American economy. With $43M in funding from Founders Fund, Greylock, Hanabi, and Dylan Field who led our Series B, we helped our customers book hundreds of thousands of jobs across services industries in North America. There are now companies operating entirely AI-first on Netic. You'll join our team with relentless builders from Scale, Databricks, HRT, Meta, MIT, Stanford, and Harvard in bringing frontier AI to the physical economy, where the problems are hard, the data is complex, and the impact is immediate and tangible. As an Applied AI Research Engineer, you'll dive deep into cutting-edge research, understand the business functions we put on autopilot inside-out, and execute targeted ML projects that deliver pure magic. What You'll Do: - Study the frontier: Track frontier work in traditional ML, LLMs, multimodal models, retrieval, and agentic systems-then distill it into ideas we can ship. - Identify high‑ROI projects: Partner with GTM and ops teams to spot bottlenecks in products; define ML projects that unlock significant leverage for customers. - Build targeted models: Own the full cycle-data curation, training, evaluation, and deployment-delivering systems that solve real customer pain points. - Productionize solutions: Integrate models into our real-time platform via robust APIs and streaming pipelines, ensuring model performance and guardrails from day one. - Self‑direct & ship: Operate like a founder-set technical roadmap, validate quickly, and iterate based on real-world results.
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