Candidate Bench
Pre-Qualified Candidates Ready for Impact
Browse vetted, confidential candidates across our six practice areas. Each has been personally evaluated by our team.
AI/ML Engineering
4 candidatesPrincipal ML Engineer
"Architected the recommendation engine serving 40M daily users — improved engagement 34%."
- 10 years in ML engineering and infrastructure
- Expert in PyTorch, TensorFlow, and distributed training
- Built MLOps pipelines processing 2TB+ daily
- Published at NeurIPS, ICML, and KDD
- Remote — US timezone
- Target: $280–340k base + RSUs
Principal ML Engineer
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Director of Data Science
"Built a 15-person DS team that generated $90M in attributable revenue through predictive models."
- 12 years spanning research and applied data science
- PhD in Statistics from a top-10 program
- Led NLP and computer vision initiatives at scale
- Strong cross-functional leadership with product and eng
- Hybrid — Bay Area or NYC
- Target: $260–310k base + equity
Director of Data Science
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Applied AI Researcher
"Developed a proprietary LLM fine-tuning pipeline that cut inference costs 60% with no quality loss."
- 8 years in NLP and generative AI research
- Co-authored 12 papers with 2,000+ citations
- Expert in RLHF, prompt engineering, and model evaluation
- Experience shipping AI products to 1M+ users
- Remote — flexible
- Target: $240–290k base + RSUs
Applied AI Researcher
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ML Infrastructure Lead
"Reduced model training costs 45% by migrating to a custom Kubernetes-based ML platform."
- 9 years in ML infra and platform engineering
- Expert in Kubernetes, Ray, and Spark for ML workloads
- Built feature stores serving 500M+ predictions/day
- Strong background in SRE and system reliability
- Remote — US-based
- Target: $250–300k base + equity
ML Infrastructure Lead
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