Senior Data Scientist / Tech Lead
New
Warszawa, Krucza 50, Kraków, Aleksandra Lubomirskiego 20, Wrocław, Świdnicka 40, Katowice, -, Gdańsk, -, Warszawa, Country code: PLFull-TimeSenior
Salary19,320 - 28,560 PLN per month
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Job Details
- Languages
- English
- Experience
- 5+ years
- Required Skills
- AWSDockerPythonSQLKubernetesMachine LearningData scienceNosqlCI/CDLLM
Requirements
- 5+ years of commercial experience in designing and implementing scalable AI solutions (Machine Learning, Predictive Modeling, Optimization, NLP, Computer Vision, GenAI, LLMs, Deep Learning).
- Proficiency in developing ML algorithms from scratch to production deployment.
- Strong programming skills in Python: writing clean code, OOP design, extensive knowledge of ML libraries (Scikit-Learn, PyTorch / Tensorflow).
- Proven expertise in deploying solutions in cloud environments (AWS or Azure).
- Knowledge in applying LLMs (AI agents, semantic search, prompt engineering, multimodal embeddings, RAG).
- High proficiency in English (C1 level).
- Excellent communication skills and consulting experience with direct interaction with clients.
- Working experience in SQL and NoSQL databases (MongoDB, Snowflake, Databricks).
- Good knowledge of CI/CD principles (GitHub and GitHub Actions).
- Familiarity with MLOps practices, Kubernetes and Docker.
- Master’s or Ph.D. in Computer Science, Data Science, Mathematics, Physics, or a related field.
Responsibilities
- Lead the development, implementation, and validation of Machine Learning solutions, ensuring alignment with project objectives.
- Lead the design of AI solution architectures that meet complex business goals and drive innovation.
- Research, test and select the best tools and technologies as well as AI solutions to meet the business requirements.
- Understand clients’ needs and translate business problems into data science problems.
- Architect and oversee the implementation of data pipelines and workflows, setting standards for data quality and security.
- Coordinate with Data Engineering and Software Engineering teams to strategize and oversee the building of AI applications.
- Present findings and recommendations clearly and concisely to stakeholders.
- Prioritize, and control tasks within an Agile/Scrum framework, ensuring timely delivery.
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