Hire · Machine Learning Engineers

Hire Machine Learning Engineers

Getting a model to work in a notebook is the easy half. Our machine learning engineers build forecasting, classification, recommendation and risk models that keep working on next month's data, with the pipelines and monitoring to prove it.

  • Senior, pre-vetted engineers only
  • You interview and choose before anyone starts
  • Working-hours overlap with India, the UK and the USA
48-hour turnaround · free · no obligation

Talk to us about hiring machine learning engineers

Tell us what you want to build. A senior engineer sends back a scope and a fixed price within two business days, no obligation.

No spam. One senior engineer, one follow-up. We reply within 48 hours.

5.0 on Clutch·200+ projects·Production AI in 3 to 8 weeks

The role

What our machine learning engineers do

What our machine learning engineers build

  • Demand forecasting and inventory models
  • Classification and document tagging models
  • Recommendation and ranking systems
  • Fraud, risk and anomaly detection
  • Monitoring for data drift and model decay

When to hire a machine learning engineer

  • You have historical data and a clear prediction to make
  • A model works in a notebook but not in production
  • Model accuracy has drifted since launch
  • You need ML skills for a defined project without a long hiring cycle

Skills

Skills and stack

  • Python
  • scikit-learn
  • XGBoost and LightGBM
  • PyTorch
  • TensorFlow
  • Spark
  • SQL
  • MLflow

Process

How hiring works

  1. 01

    Share your needs

    Tell us the stack, the problem and how you want to work. We confirm fit on a short call.

  2. 02

    Interview the shortlist

    We send profiles of pre-vetted senior engineers who match your stack and domain. You interview and choose.

  3. 03

    Onboard and ship

    Your engineers onboard and start delivering without a long recruiting cycle, with working software at the end of each sprint.

Engagement models

Three ways to work with us

Staff augmentation

Add one or two senior engineers to your existing team to close a specific skill gap. Your leads, our specialists.

Dedicated team

A small senior team working only on your roadmap, with a lead who owns delivery.

Defined project

A scoped build such as a RAG system, a model or a pipeline, delivered to an agreed outcome.

Related work

See similar systems in production

FAQ

Hiring machine learning engineers: FAQs

What does a machine learning engineer do?

A machine learning engineer turns data into models that make predictions, then builds the pipelines to train, deploy and monitor them in production. Compared with a data scientist, the focus is on reliability, performance and integration with live systems.

Do I need a lot of data to start?

Not always. Many forecasting and classification problems work with the data you already have. A short scoping step tells you whether your data is enough and what accuracy to expect.

Can your ML engineers work inside our team?

Yes. You can add one or two senior engineers to your existing team, take a dedicated team, or hand us a defined project.

How do you keep models accurate after launch?

We monitor input data and prediction quality, alert on drift, and set up retraining pipelines so accuracy does not silently decline.

Which time zones do you cover?

Our senior engineers are headquartered in Ahmedabad and work with clients across India, the UK and the USA with working-hours overlap.

Get your exact number with a free 48-hour audit

Indicative ranges only get you so far. Tell us the specifics and get a scope and a fixed price in two business days.