AI & ML Engineering Talent
A capability overview of the AI and ML engineering roles we recruit: what each one owns, how the talent pools differ, and where teams usually mis-scope the hire.
Hiring machine learning engineers specifically? See Machine Learning Recruiters. Building a full AI org or hiring AI leadership? See our AI recruiting practice.
Roles We Specialize In
Individual-contributor and staff-level ML, AI, and platform engineers who ship in production.
Machine Learning Engineers
ML engineers who design, train, and deploy production models — from feature pipelines and training loops to online serving at scale.
Applied AI Engineers
Practitioners who ship LLM, RAG, and agent features into product — turning research prototypes into reliable user-facing systems.
Data Scientists
Statistical modelers and experimentation leads who drive product decisions, build predictive models, and own the analytics stack.
MLOps Engineers
Platform engineers who own model training infrastructure, CI/CD for ML, feature stores, evaluation harnesses, and production monitoring.
AI Infrastructure Engineers
Systems engineers who build GPU clusters, inference platforms, distributed training, and low-latency serving for foundation-model workloads.
Founding AI Infrastructure Engineers
First infrastructure hires for AI startups who design cost-efficient serving, training pipelines, and platform foundations from day one.
Find the right practice for your search
AI and ML hiring is not one market. Start with the practice that matches the role you are filling.
Hiring machine learning engineers
Ranking, NLP, computer vision, speech, and ML platform searches each draw from a different pool. The dedicated ML practice covers screening and current comp bands.
Machine Learning RecruitersBuilding a full AI team or hiring AI leadership
Broad AI recruiting: applied AI, LLM engineering, research, infrastructure, and AI leadership across one engagement.
AI recruiting practiceHiring product-facing AI engineers
Applied AI and LLM engineers who ship agent, RAG, and evaluation features into production products.
AI Engineer RecruitersHiring agent or forward deployed engineers
Agentic systems and customer-facing deployment engineering are separate skill sets from core model work.
Agentic AI RecruitersHiring GPU, training, or inference platform engineers
Distributed training, cluster operations, and low-latency serving sit in the AI infrastructure pool.
AI Infrastructure RecruitersHiring research engineers or scientists
Foundation model research and post-training work is credentialed and screened differently from applied engineering.
AI Research Engineer RecruitersHiring AI or ML engineers?
Tell us the roles, stack, and stage. We will map the search to the right talent pool and give you a realistic timeline in a 30-minute call.
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