Tier 3 · Developers & Engineers
Hire a Machine Learning Engineer. Embedded in your team.
Build and train models, not just call them. Custom ML, fine-tuning, and production deployment. From $35 an hour, working your hours, in your stack.
What a Machine Learning Engineer does
There is a clear line between Tier 2 and Tier 3. A developer calls a model through an API. A machine learning engineer builds the model.
This tier is for teams that need real machine learning: a model trained on your own data, fine-tuned to your task, evaluated for accuracy, and deployed so it runs reliably in production. It covers the full path, from preparing data to shipping a model your product depends on.
If an off the shelf API answers your need, you do not need this tier and should not pay for it. When you need something an API cannot give you, this is the tier.
What they build
Models that are yours, in production.
- Custom machine learning model development and training
- Fine-tuning language models on your own data
- Computer vision: detection, classification, OCR
- Natural language processing: extraction, classification, sentiment
- Recommendation engines
- Forecasting and predictive models
- Data pipelines that feed and retrain models
- MLOps: training, deployment, monitoring, and retraining
- Model evaluation and accuracy testing
Core modeling, plus the deployment and scale stack: Docker, MLflow, vector databases such as Pinecone and Weaviate, and cloud ML platforms including AWS SageMaker, Google Vertex AI, and Azure ML.
Example projects
An AI startup fine-tunes a language model on their proprietary data so it performs on their specific task, not a generic one.
A product team builds a computer vision pipeline that classifies images inside their app in real time.
A marketplace builds a recommendation engine that lifts what users find and buy.
An operations team builds a forecasting model that predicts demand and reduces waste.
Choose a Machine Learning Engineer when calling an existing API is not enough, and you need a model built, trained, or fine-tuned on your own data. If your use case is solved by an LLM API, Tier 2 builds that for less. If you are unsure where your project lands, the discovery call will place it.
Not sure which tier you need? Book a call and we will map it for you.Pricing
One rate. Everything included.
| Engagement | Rate | Monthly |
|---|---|---|
| Full-time, 40 hrs/week | $35/hr | $5,600/mo |
| Part-time, 20 hrs/week | $35/hr | $2,800/mo |
All prices in USD. No setup fees, no markups, no hidden costs. A machine learning engineer in the US commonly costs well over $150 an hour.
What you get with every placement.
Pre-vetted talent
Free replacement
Time tracked with software
Dedicated account manager
Trained on your tools
No hidden fees
How to get started
Onboarded in days, not months.
Discovery call
Tell us what you need built or trained.
Interview
Meet your shortlisted candidates and pick the fit.
Onboarding
Your engineer is working within 24 to 48 hours.
Questions, answered.
Other tiers
Need less? Compare the lighter tiers or see the full overview.
Ready to build a model that is yours?
Book a discovery call. Tell us what you need built or trained and we will match you with the right engineer.
Book a discovery call