Hire Devs · AI
Machine learning engineers for forecasting, classification, recommendation and model pipelines.
Our ML developers build models that hold up outside the notebook: clean feature pipelines, reproducible training, proper validation and monitoring for drift once the model is live.
- Demand and revenue forecasting
- Churn, fraud and risk scoring
- Recommendation and ranking systems
- Computer vision with OpenCV and deep learning
- Feature stores and training pipelines
- Model monitoring and retraining jobs
The tools our ML Developers use every day, plus the testing, CI and monitoring every production team needs.
Modelling
- Python
- scikit-learn
- XGBoost
- LightGBM
- PyTorch
- TensorFlow
- Keras
- OpenCV
Data
- pandas
- NumPy
- Polars
- Apache Spark
- Dask
- Jupyter
- DuckDB
Platforms
- Databricks
- Snowflake
- BigQuery
- Apache Airflow
- Ray
Serving and observability
- FastAPI
- Docker
- Kubernetes
- MLflow
- Weights & Biases
- Langfuse
- Sentry
001
Senior and vetted
Every engineer passes technical interviews, a paid trial task and reference checks before joining a client.
002
Start in days
We shortlist matched profiles quickly, and you interview them before anyone starts.
003
Your hours, your tools
Engineers work in your Slack, Jira and GitHub with a guaranteed overlap with your timezone.
004
No lock-in
Scale up, scale down or swap an engineer with simple notice. You own all code and IP.
Pick the model that fits your stage. Switch as you grow.
Individual Experts
Plug a senior specialist into your team for focused, hourly work.
- Specialist expertise, on demand
- Transparent hourly rates
- Flexible engagement length
Project Packages
A scoped engagement with clear milestones, owners and outcomes.
- Fixed scope & timeline
- Milestone-based delivery
- Predictable investment
Retainer / Custom
Ongoing partnership across software, marketing and finance.
- Dedicated cross-discipline team
- Scale up or down as needed
- Priority, long-term support
Step 001
Share your needs
Tell us the role, stack, seniority and timeline.
Step 002
Meet your matches
We send vetted profiles and you interview the ones you like.
Step 003
Start a trial
Begin with a short trial period to confirm the fit.
Step 004
Scale with confidence
Add engineers or adjust the team as your roadmap changes.
What teams usually ask before hiring ML Developers through us.
Yes. They package models behind APIs or batch jobs, track experiments in MLflow or Weights & Biases, and set up monitoring for drift.
That is normal. Most projects start with data cleaning and a baseline model to prove value before heavier modelling.
Most clients see matched profiles within a few business days of the first call, and the chosen developer can usually start the following week.
Yes. You review profiles, run your own technical interview and only developers you approve join your team.
Rates depend on seniority, skills and engagement length. You get a clear monthly or hourly rate before anyone starts, with no recruitment or placement fees.
Tell us and we will replace them at no extra cost, with a handover so your work keeps moving.
They join your Slack or Teams, Jira or Linear and GitHub, attend your stand-ups and follow your processes, with an agreed daily overlap with your timezone.
You own all code and IP from day one. Developers sign NDAs, work in your accounts with least-privilege access, and we remove access when the engagement ends.
Yes. Add developers as your roadmap grows or reduce the team with simple notice. There are no long lock-in contracts.
Tell us about the role and we'll send matched profiles.