Nice place to learn but not to stay - Machine Learning Engineer Factored Employee Review

3.0
11 Aug 2025
Recommend
CEO approval
Business outlook

Pros

Talented, collaborative teams with strong knowledge sharing. Exposure to international client projects that accelerate learning (ML/MLOps, Azure/AWS, Databricks). Flexible remote culture; solid code review practices and quality standards. Technical leadership generally accessible and open to mentorship when needed. Decent documentation and internal forums (tech talks, guilds) that add value.

Cons

Compensation below market for senior LATAM profiles; adjustments can be slow. Project placement can take time; bench periods create uncertainty and fatigue. Career paths and levels not always transparent; promotions feel unpredictable. Perceived lack of transparency from the CEO regarding projected equity value for employees; assumptions about valuation, dilution, and exit scenarios are not clearly communicated. You can't work outside your country. Pressure to take on additional internal work (proposals, interviews, content) even while fully staffed on a client, with no extra compensation or benefits; unclear boundaries lead to context switching and burnout risk.

Explore other reviews about Factored

4.0
9 Jun 2026
Recommend
CEO approval
Business outlook

Pros

- Process was clear, and a lot of information was provided between rounds - People is super gentle, and will guide you through the rounds

Cons

- Process was a bit slow to have the first meeting, then was speeding fast - The initial questionary is pretty big, last about 3 hours

3.0
27 May 2026
Anonymous employee
Recommend
CEO approval
Business outlook

Pros

Factored is a good place to work. The CEO is very transparent and honest, and while salaries are not particularly high, I do think there are good learning opportunities.

Cons

There can be a sense of favoritism among Colombian employees. It may not be very obvious at first, but over time it can feel that way. There are also several family members and even couples working in nearby teams, which may create some concerns around fairness and objectivity.

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