AI/ML STAFFING & TALENT VALIDATION
A GREAT RESUME CAN HIDE A LOT.
AI experience is easy to claim. Mitchell Martin combines job-specific technical assessment, identity verification, fraud detection, and experienced recruiter review to show you what’s behind the résumé.
What Makes This Different
BUILD THE TEAM ON PROVEN CAPABILITY
Nearly one-third of job seekers say they have claimed AI skills they do not actually have. Another 28% say they have used AI to generate fake work samples. When your first AI hire can shape the team and the work that follows, deeper validation matters even more.
MMI goes beyond traditional screening with a process designed to verify both the candidate and the capability before they reach your team.
JOB-SPECIFIC TECHNICAL ASSESSMENT
Built around the actual requirements of the role, not a generic test.
IDENTITY VERIFICATION
Helps confirm the person being evaluated is the person you are considering.
FRAUD DETECTION
Adds another layer of protection against suspicious behavior, misrepresented work, and other integrity concerns.
The Human Side of AI Hiring
THE RIGHT SKILLS DON’T ALWAYS MEAN THE RIGHT HIRE.
The future of AI is human, and so is every great hire behind it. MMI’s recruiters bring four decades of deep technical placement expertise to every search, from the first conversation to the final decision.
START WITH PROVEN CAPABILITY
Begin with candidates who have already demonstrated the skills the role requires.
FOCUS ON THE RIGHT FIT
Technical validation gives our recruiters more to work with before deciding who should reach your team.
BRING EXPERIENCE TO THE DECISION
Our recruiters know how to evaluate technical talent beyond a score or a résumé.
Tested and Verified Talent
SEE THE AI TALENT WE’RE WORKING WITH
A sample of the professionals companies are hiring as they build out early AI teams.
AI / ML ENGINEER
4 years of experience building and deploying machine learning and GenAI solutions across financial and operational environments. Hands-on with RAG, LLM fine-tuning, NLP, predictive modeling, MLOps, and production deployment across AWS, Azure, and GCP.
Core experience: RAG, LangChain, GPT-4/Claude, PyTorch, TensorFlow, XGBoost, Docker, Kubernetes, MLflow, AWS
AI ENGINEER / DATA SCIENTIST
3.6 years of experience building and deploying enterprise AI/ML solutions across healthcare, retail, manufacturing, and financial services. Hands-on with GenAI, RAG, multi-agent systems, predictive modeling, time-series forecasting, and production MLOps.
Core experience: LangGraph, RAG, OpenAI, AWS Bedrock, Python, XGBoost, PyTorch, MLflow, FastAPI, Kubernetes, AWS, Azure
ML PLATFORM / AI INFRASTRUCTURE ENGINEER
5+ years of experience building and scaling production ML infrastructure, model-serving platforms, and real-time AI systems. Hands-on with RAG, distributed inference, Kubernetes, RayServe, KServe, Triton, and large-scale streaming environments.
Core experience: Python, PyTorch, TensorFlow, RAG, RayServe, KServe, Kubernetes, MLflow, Kafka, Flink, AWS
LET’S TALK ABOUT YOUR AI HIRING NEEDS
Whether you have an open role or are planning your next hires, talk with our AI recruiting team about the skills you need and the talent available.
