New Roles · Engineering AI Builders
ML Engineer. The role, the market signal, and how to build it in your org.
The pre-agentic AI Builder. Still the largest single bucket, model training, evaluation, deployment. Increasingly overlaps with AI Engineer and Applied AI roles.
In a workforce of people and AI agents, this role takes shape around the workflows it supports. Define its responsibilities and handoffs, then prepare people to perform that work.
881 postings · 491 distinct titles · from 264,613 real job postings · see the live data →
What the market calls it
Machine Learning EngineerSenior ML EngineerStaff ML EngineerML Developer
Hiring this role in our corpus right now
Accenture 162Waymo 60Capitalone 49Adobe 45Generalmotors 41
What the postings ask this role to do
14,007 tasks extracted from real ML Engineer job descriptions, classified Automate / Augment / Human-only. Only 2.7% can be fully automated: companies are hiring this role for the judgment, not the keystrokes.
Automate
- Monitor models in production.
- Retrain models in production.
- Automate tests and deployment
- Set up alerts and dashboards.
- Containerize models with docker.
Augment
- Develop applications and systems that utilize ai tools and cloud ai services.
- Apply genai models as part of the solution.
- Construct optimized data pipelines to feed ml models.
- Maintain models in production.
- Conduct statistical analyses on business processes using machine learning techniques.
Human-only
- Make team decisions.
- Engage with multiple teams and contribute to key decisions.
- Collaborate and manage the team to perform.
- Engage with multiple teams and contribute on key decisions.
- Govern models from a risk perspective.
How we build it in your org
From the market's version of this role to your version of it
1. Define workflow responsibilities
Start with the workflows this role supports: the outcomes, decisions, and handoffs it owns. Task Intelligence examines the tasks within that work and how people and agents can share responsibility.2. Define your version
Your team composes the job description for your org's variant of the role, grounded in those responsibilities and the task evidence rather than a copied template.3. Practise and assess readiness
Build on the domain and technical expertise your people already bring. Use relevant Simulations, GenAI Sandboxes, and Skill Validation Assessments to practise changed responsibilities and demonstrate capability. Revisit preparation when the work changes.Start with the work, not the org chart.
Define what this role will own, then connect those responsibilities to practice and assessment.