Offer summary

Qualifications:

3+ years of experience in data science, MLOps, or similar roles., Proven experience in product management or collaboration within product teams., Strong analytical skills and proficiency in Python and related tools., Excellent communication skills and an entrepreneurial spirit..

Key responsibilities:

Design and lead the product roadmap based on data and user feedback.

Translate analytical insights into concrete product features and improvements.

Participate in technical implementation and collaborate with the engineering team.

Conduct product discovery processes and analyze market trends to identify opportunities.

Job description

This is a remote position.

About the Role

We’re looking for a hybrid builder-strategist to lead the development of our AI products from vision to execution. As a startup deeply committed to responsible AI, we need someone who can wear multiple hats: define product strategy, engage with users, and contribute directly to technical implementation. This role is ideal for someone who thrives in dynamic environments, enjoys end-to-end ownership, and wants to shape impactful, ethical technology from the ground up.

Requirements

3+ years of experience in data science, MLOps, LLMOps, or similar technical roles.
Proven experience in product management or direct collaboration within product teams.
Strong analytical skills
Python.
Additional tools: FastAPI, MLServer, Flask, TensorFlow, or PyTorch.
Experience with classification and regression algorithms.
Ability to translate complex models into understandable and usable solutions.
Excellent communication skills and ability to collaborate across disciplines.
Entrepreneurial spirit, results-oriented, and autonomous
Willingness to travel (less than 10%).
Fluent in English (C1 level).

Responsibilities

Design and lead the product roadmap, prioritizing initiatives based on data, user feedback, competitive analysis, and strategic objectives.
Translate analytical insights and machine learning models into concrete features, improvement proposals, or new products.
Actively participate in the technical implementation of the product, collaborating with the engineering team or writing code directly (as needed).
Research and analyze market trends, benchmarks, and competition, anticipating opportunities and risks.
Conduct product discovery processes, validating hypotheses with real users, data, and functional prototypes.
Analyze systems to detect risks and vulnerabilities.
Evaluate results and model behavior by analyzing performance, drift, bias, and feature importance.
Analyze Generative AI systems to assess the risks of these applications aligned with the EU AI Act and the NIST AI Risk Framework. Ability to detect hallucinations, sentiment, moderation, and apply prompt engineering for the creation of LLM-as-a-judge systems.