Nice place to learn but not to stay - Recensione dipendente - Machine Learning Engineer presso Factored

3,0
11 ago 2025
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

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.

Svantaggi

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.

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4,0
9 giu 2026
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

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

Svantaggi

- 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 mag 2026
Dipendente anonimo
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

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.

Svantaggi

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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