Design, build, and productionize NLP-heavy machine learning systems, including text classification, entity extraction, semantic similarity, and LLM-based workflows;
Write clean, efficient, and testable Python for data pipelines, feature engineering, modeling, and evaluation;
Own models end-to-end: problem framing, data exploration, modeling choices, validation, deployment, and iteration;
Work closely with product, engineering, and UX to turn ambiguous problems into concrete, data-driven solutions;
Evaluate and apply modern NLP approaches, from classical methods to transformer-based and generative models, with a pragmatic bias toward impact;
Communicate findings clearly to both technical and non-technical stakeholders, focusing on decisions, trade-offs, and outcomes rather than theory.

Requirements

Proven experience in applied data science or machine learning, with clear ownership of shipped models;
Strong NLP background, including hands-on experience with text modeling, embeddings, transformers, or LLM-based systems;
Advanced Python skills: you write production-quality code;
Solid SQL skills and experience working with large, imperfect, real-world datasets;
Strong understanding of machine learning fundamentals, model evaluation, and failure modes;
Ability to translate business problems into modeling approaches, and to explain results without hiding behind jargon;
Experience working in modern engineering environments (code reviews, testing, version control, CI/CD).

Benefits

Growth and learning opportunities: time dedicated to learning, conferences, online learning platforms, and books for your professional development;
Health and wellness: we want you to feel and be your best. That's why we offer various benefits, from online workouts, a physical coach and a gym to regular mental health checks;
Tools of your choice: choose technical equipment and the tools you need to do your best;
Community and celebrations: get ready for long-lasting traditions such as yearly workation, Friday get-togethers, various team buildings and company celebrations;
Convenient commuting: traveling from point A to point B can be a pain. That’s why, depending on your unique circumstances, we compensate part of your public transport costs;
Work-life balance: We encourage working in the office, with the possibility of up to two remote days per week. Plus, with our WFA policy, you can work from almost anywhere in the world;
Premium Surfshark accounts: for you, your family, and friends;

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

NLPmachine learningtext classificationentity extractionsemantic similarityPythonSQLmodel evaluationtransformersLLM-based systems

Soft Skills

problem framingdata explorationcommunicationtranslating business problemscollaborationdecision-makingtrade-offs analysisiterationexplaining resultsadaptability