“DJ is phenomenal. They find amazing candidates, make hiring extraordinary devs easy. Think of it as having a top recruiter, HR, and payroll departments in dozens of countries.”
Get a curated shortlist of senior Scikit-learn engineers in 2 weeks. We headhunt senior scikit-learn and Python ML engineers who join your team remotely, on-site, or through relocation. Expect US time-zone overlap, evidence-based vetting, and a money-back guarantee.
Andres
Recruitment Expert
Verified
Problem framing & data sense: turns vague goals into measurable targets; guards against leakage and scope creep.
Feature engineering that lasts: Pipeline
/ColumnTransformer
, robust encoders/imputers, reproducible transforms.
Honest validation: stratified CV, time-series splits, proper baselines; understands imbalanced data and calibration
Model practicality: picks the simplest model that wins (linear/trees/GBM/SVM), documents trade-offs, delivers model cards.
MLOps basics: packages models behind FastAPI/Flask, containers (Docker), CI checks, versioning, simple monitors for drift/decay
Remote-readiness: clear async writing, soft skills, dependable U.S./Canada overlap.
Maya
Senior ML Engineer (scikit-learn)
Specializes in turning raw business data into production-ready models with clear, explainable results. Strong at feature engineering, honest validation, and choosing the simplest model that meets the goal.
Diego
Applied Data Scientist (scikit-learn)
Focuses on fast, reliable baselines and measurable wins on tabular/NLP problems. Skilled at building end-to-end pipelines—from data prep to evaluation to dashboards—so stakeholders can see lift, not just accuracy.
Mario
ML Ops-minded Data Scientist
Known for making models easy to run, monitor, and improve over time. Sets up repeatable training and scoring workflows, versioning, and simple health checks (data drift, performance alerts) so teams trust the output.
Testimonials
As a leading remote IT recruitment agency, we care that our clients take part throughout the hiring process. Why? Because for us, hiring a qualified candidate is not only about the skills and abilities, but it’s also about how candidates match with your company’s culture.
As soon as you talk with us or fill our form, the first thing we do is analyze your company. We want to understand your culture and the type of people you value working with.
In 2 weeks, you’ll start reviewing people that match your requirements. We focus on providing you 3-5 top candidates instead of giving you an endless list.
Once you select the candidate, we handle all the contracts, NDA’s and payments from day 1.
We proactively source across global markets and triage applicants based on their expertise, salary band, U.S. time-zone overlap, English fluency, and long-term availability.
A recruiter assesses English proficiency, async communication, culture add, motivation, and availability. We verify work history and stability (no serial short stints).
Practical task (90–120 min): build a scikit-learn Pipeline
for a real-world tabular problem; include CV, metrics, calibration, and a lightweight API.
Senior engineers run a live session vetting their skills.
We speak with past stakeholders and review code artifacts where possible. We confirm achievements, ownership level, and reliability in distributed teams.
We align on start date, hardware/security constraints, preferred collaboration tools, and, when needed, relocation logistics inside the US.
Model | Best For | What You Get | Trade-offs |
---|---|---|---|
DistantJob (Placement) | Long-term ownership | Full-time NumPy/Python dev in your team; U.S. overlap; HR handled | Not for one-off gigs |
Outsourcing agency | Managed project | Vendor team delivers scope | Less control, vendor IP/process |
Marketplace/freelancers | Short tasks | Fast, flexible | Turnover; you manage vetting/compliance |
Job boards/DIY | Big applicant pools | Control | Slow; heavy screening work |
No. We place full-time remote employees who work in your repos and rituals.
Most teams onboard a scikit-learn developer in 2–4 weeks.
Yes, the shortlists prioritize dependable overlap and strong async communication.
Yes: global contracts, NDA, payroll, benefits, and compliance are included.
Best way to hire a scikit-learn developer in 2025 require reproducible pipelines, honest validation, clear model cards, and a simple API/CI path to production—then review real artifacts before interviews.
Ready to hire the best developers, 40% faster than the industry average? Give us your email, and our account manager will get in touch ASAP!
When you partner with DistantJob for your next hire, you get the highest quality developers who will deliver expert work on time. We headhunt developers globally; that means you can expect candidates within two weeks or less and at a great value.
Increase your development output within the next 30 days without sacrificing quality.