Machine Learning Engineer

What you'll do

Unlike most micro1 listings, which have you grade or write tasks for a model, this ad reads like hands-on ML engineering inside a training project. You design and refine models in Python, use MongoDB to store and retrieve the data they train and validate on, and build the preprocessing and data pipelines between the two.

Evaluation is a large part of it: tuning hyperparameters, benchmarking results and measuring against the right metrics. Every experiment gets written up so the workflow is transparent and repeatable, and you turn the findings into recommendations for the rest of the project.

The ad does not name the customer or the kind of model, so ask what problem the models are solving and whether the work is building them or evaluating them.

Who fits

• Strong Python, with real depth in scikit-learn, TensorFlow or PyTorch
• Hands-on MongoDB for storing, manipulating and retrieving ML data
• A record of delivering ML solutions in real settings
• Good grasp of evaluation metrics, feature engineering and preprocessing
• Experience deploying or operationalising models in cloud or enterprise environments
• Clear technical writing
• Comfortable adapting to changing requirements in a remote team

What it pays

$80–140/hour, micro1's published figure. No pay structure, weekly hours or placement criteria are stated.

micro1 also lists an ML Engineer role at $100–150/hour; the MongoDB requirement is what sets this one apart.

Worth knowing

Good:

• Real engineering work, not only rating model output
• MongoDB experience, uncommon among ML candidates, is a named advantage
• 35 openings
• Remote

Less good:

• The MongoDB requirement narrows the field and is non-negotiable in the ad
• Pay structure and hours not stated
• Customer and model type not named
• Contractor engagement: no benefits, your own tax to manage

About this listing

Posted by micro1 on its own jobs portal and read on 24 September 2026. Location is Remote with no country list. See micro1.