Hire Dedicated Machine Learning Engineers
Add a vetted machine learning engineer to build, train and evaluate prediction, classification and forecasting models against your own data.
50+ ERP and software projects. Zero failed projects since 2021.
A model that looks good in testing can still fail in production
Real data is messier than a clean benchmark dataset, and accuracy drifts as your business changes. Someone has to own that ongoing work.
Not a demo model, one trained on your business
A model trained on a generic dataset rarely performs well on your actual sales, inventory or support data. A dedicated machine learning engineer trains and tunes the model specifically against what your business produces.
- Models trained on your own historical data.
- Clear metrics agreed before training starts.
- Honest reporting on where accuracy falls short.
Accuracy drifts, so someone has to keep watching
Customer behavior, seasons and product mixes change, and a model that was accurate at launch can quietly get worse. A dedicated engineer monitors this and retrains before it becomes a business problem.
- Ongoing monitoring for accuracy drift.
- Retraining scheduled before performance drops.
- Alerts if a model starts behaving unexpectedly.
Metrics you can hold the model to
Every model is scored against agreed metrics before it goes live, and again on a regular schedule after.
From requirements to a working engineer in about two weeks
Everything you need to run the engagement smoothly
Dedicated to your project
The engineer works only on your account, not split across other clients' models.
Direct communication
You talk to the engineer directly on your tools, with no account manager relay in between.
Flexible contracts
Full time, part time, or a fixed scope of work. Scale up or down with notice, not a long lock-in.
Metric-based reviews
Model performance reviewed against the metrics agreed before training started.
Timezone overlap
Working hours arranged to overlap with your team for stand-ups and reviews.
Replacement guarantee
If the engineer is not the right fit, we replace them at no extra cost during the engagement.
What a dedicated machine learning engineer changes for your models
Why teams hire machine learning engineers through TCB Infotech
Hiring machine learning engineers, answered
What does a dedicated machine learning engineer do?
How is this different from an AI engineer?
Do you work with our existing data as it is?
How do you know if the model is actually working?
What is the engagement model?
What if the engineer is not the right fit?
Hire a Dedicated Machine Learning Engineer
Book a free consultation. Tell us what you need predicted or classified, and we will shortlist engineers who fit your data and your team.
Book a Free Consultation →No commitment. See a shortlist before you decide.
How Hiring a Dedicated Machine Learning Engineer Works
From the requirements call to a model tracked against real metrics. Here is how we vet, match and onboard every machine learning engineer we place.
Vetting, matching and onboarding, in that order
Every engineer is tested on real model work
Before an engineer joins our bench, they are tested on data preparation, feature engineering, model evaluation, and a hands-on task training and scoring a model against a realistic dataset. Only engineers who pass are shortlisted to clients.
- Data preparation and feature engineering.
- Model training and evaluation task.
- A realistic messy-data exercise.
You get a shortlist, not a resume pile
We match engineers to your specific problem: the type of prediction you need, the data you have, and the timezone overlap that works for your team. You see 2 to 3 fitting profiles, not fifty.
- Matched to your prediction problem.
- Matched to the data you actually have.
- Matched to your working hours.
A structured start, then you take the lead
The engineer reviews your data, agrees the success metrics with you, and starts on the first model in the first week. You manage priorities directly from there.
- A review of your data quality and gaps.
- Agreed success metrics before training starts.
- Direct day-to-day management by your team.
Everything included in the engagement
Dedicated engineer
Works only on your account, not shared across other clients' models.
Direct communication
Access to the engineer on your own tools, with no account manager relay.
Flexible contracts
Full time, part time, or a fixed scope, adjustable with notice as your roadmap changes.
Metric-based reviews
Performance reviewed against the metrics agreed before training started.
Timezone overlap
Working hours arranged to overlap with your team for stand-ups and reviews.
Replacement guarantee
A new engineer at no extra cost if the current one is not the right fit.