Addepto

Lead Data Scientist / ML Engineer

19.3k - 28.6k PLN19 320 - 28 560 PLN/ mies./ mies.B2BB2B (netto)

SeniorZdalnie·WarszawaFull-time·B2B

#460826·Dodano 19 dni temu·5

Źródło: justjoin.it

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Tech Stack / Keywords

Machine Learning LLMCloudAIPython Generative AIData Science

Podsumowanie oferty

Lead the development and validation of Machine Learning solutions and design AI architectures for client projects, including an airport-operations optimization engine and an LLM recommendation engine. The role involves translating client needs into data science problems and overseeing data pipelines and AI applications using technologies such as Python, AWS and Azure.

Wymagania

7+ years of commercial experience designing and implementing scalable AI solutions, including Machine Learning, predictive modeling, optimization, NLP, computer vision, GenAI, LLMs, and deep learning.
Proficiency in developing ML algorithms from scratch through production deployment.
Strong Python programming skills, including clean code, OOP design, and extensive knowledge of Scikit-Learn, PyTorch, or TensorFlow.
Proven expertise deploying solutions in cloud environments using AWS or Azure.
Knowledge of applying LLMs, including AI agents, semantic search, prompt engineering, multimodal embeddings, and RAG.
High proficiency in English (C1).
Excellent communication skills and consulting experience involving direct client interaction.
Experience with SQL and NoSQL databases, including MongoDB, Snowflake, or Databricks.
Good knowledge of CI/CD principles and 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.

Nice to have:

Experience with Big Data technologies such as Spark, Hadoop, and Kafka.

Obowiązki

Lead the development, implementation, and validation of Machine Learning solutions aligned with project objectives.
Lead the design of AI solution architectures for complex business goals.
Research, test, and select tools, technologies, and AI solutions to meet business requirements.
Understand clients’ needs and translate business problems into data science problems.
Architect and oversee data pipelines and workflows, setting standards for data quality and security.
Coordinate with Data Engineering and Software Engineering teams on building AI applications.
Present findings and recommendations to stakeholders.
Prioritize and control tasks within an Agile/Scrum framework.

Benefity

Language classes.
Sponsored training and conferences, including training materials and certifications through partnerships with Databricks and Anthropic.
Team-building events and an integration budget.
Medical and sports packages, eye care, and well-being support services, including psychotherapy and coaching.

Kursy językowe

Dofinansowanie szkoleń

Budżet konferencyjny

Spotkania integracyjne

Opieka zdrowotna

Karta sportowa

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