Talent Vector Labs

AIAI talent lab for AI/ML teams

Hire the people who build AI.

Talent Vector Labs is a specialist recruitment and talent-management partner for AI and machine-learning teams. We find, vet and grow the engineers, scientists and leaders who turn models into products.

Hire AI talent Upskill your team
  • LLM
  • ML
  • MLOps
  • Data
  • Research
  • AI leadership

01Perspective

A CV lists frameworks. We find out who can ship.

AI hiring breaks the usual recruitment playbook. Titles mean different things at every company, the tooling changes every quarter, and the gap between someone who has fine-tuned a model and someone who has run one in production is invisible on paper.

We work only in AI and machine learning, so we know the questions that separate the two — and we ask them before a candidate ever reaches your calendar.

02Expertise

From first search to long-term growth.

One partner across the whole talent lifecycle of an AI team.

  1. 01Find

    Search AI talent

    Targeted search across LLM, ML, MLOps, data and research — drawing on a network built entirely around AI.

    • Retained search
    • Contingent search
    • Contract & permanent
    • Team builds
  2. 02Assess

    Vet for real-world skill

    Practitioner-designed technical assessment that tests what the role actually needs, from model evaluation to production systems.

    • Technical screening
    • Take-home review
    • Systems interviews
    • Deep references
  3. 03Grow

    Manage AI talent

    Talent management built for AI teams: retention, career pathing, compensation benchmarking and team design.

    • Retention
    • Career pathing
    • Comp benchmarking
    • Org design

03Roles we place

The roles we place.

Hands-on, specialist and leadership roles across the AI stack — permanent or contract.

  • ML Engineer

    Builds, trains and ships models into products.

  • LLM / GenAI Engineer

    RAG, agents, fine-tuning and evaluation of language models.

  • Applied Scientist

    Turns research ideas into measurable product gains.

  • Research Scientist

    Pushes the state of the art in models and methods.

  • MLOps / ML Platform Engineer

    Pipelines, serving, monitoring and infrastructure for ML at scale.

  • Data Engineer

    The reliable data foundations every model depends on.

  • AI Product Manager

    Decides what to build with AI, and why.

  • Head of AI / AI Leadership

    Sets the strategy and builds the team to deliver it.

04Approach

How an engagement runs.

Four steps, built around the work your team actually does.

  1. 01

    Calibrate

    We start with the problem, not the job description: what the team is building, the skills that matter and what great looks like.

  2. 02

    Source

    Targeted search through our AI-focused network and direct outreach — no CV spraying.

  3. 03

    Vet

    Practitioner-led technical assessment, so every shortlisted candidate has already shown the core skills.

  4. 04

    Place & grow

    Offer support, onboarding check-ins and ongoing talent management after the hire.

05Upskilling

Build AI talent, as well as hire it.

Not every capability gap needs a new hire. Talent Vector Labs Upskilling runs practitioner-led programmes that grow AI skills inside the team you already have.

  • LLM EngineeringIntermediate
  • MLOps & DeploymentIntermediate–Advanced
  • AI for Product & Business LeadersFoundation
  • Responsible & Applied AIAll levels
Explore upskilling

06Contact

Tell us who you need.

Share the role or team you're building. We'll come back with how we'd approach the search — and whether we're the right partner for it.

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