Lead Machine Learning Engineer
AI in this role
Key Responsibilities
What you’ll do:- Build and maintain production-grade ML systems and pipelines
- Stay hands-on (coding, reviews, debugging, deployments)
- Mentor a small team of ML engineers (2–3 people initially)
- Establish ML engineering & MLOps best practices
- Improve deployment, monitoring, and model lifecycle management
- Collaborate with DS, Risk, Product, and Engineering
- Help shape roadmap and hiring
Skills, Knowledge & Expertise
- Strong background as an ML Engineer (not purely DS/research)
- Experience deploying and running ML models in production
- Solid software engineering skills (Python, APIs, systems)
- Good understanding of MLOps stack (CI/CD, monitoring, pipelines)
- Familiarity with tools like MLflow, Airflow, Evidently, DVC, Docker, Kubernetes.
- Cloud experience (AWS/GCP/Azure)
- Some mentoring/leadership experience + desire to grow into management
- Nice to have:
- Experience scaling ML platforms or teams
- Fintech / lending / risk domain exposure
How we rate this
Lead Machine Learning Engineer at YouLend rates 98 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Walk me through how you've used Mlflow in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: ML Ops and Mlflow. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
Want an expert to read your CV for this job?
Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.
Get a free CV reviewGet new machine learning engineer jobs (Builds AI ●●●●) by email
One email a week with the new machine learning engineer jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free. One email a week. Unsubscribe in one click.
Similar roles
Data roles that build AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step