Addepto

Lead Data Scientist / ML Engineer

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

SeniorZdalnie·WarszawaFull-time·B2B

#460719·Dodano 19 dni temu·2

Źródło: nofluffjobs.com

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Tech Stack / Keywords

AIML algorithmsML librariesLLMs SQLNoSQLCI/CD Python GenAI AWSMLOpsDocker KubernetesAI Agents

Podsumowanie oferty

As a Lead Data Scientist / ML Engineer, you will lead the development and design of AI and Machine Learning solutions. Projects include an AI optimization engine for airport operations and an AWS-powered recommendation engine using LLMs.

Wymagania

5+ 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 programming skills in Python, including clean code, OOP design, and extensive knowledge of Scikit-Learn, PyTorch, and TensorFlow.
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).
Communication skills and consulting experience involving direct interaction with clients.
Working experience with SQL and NoSQL databases, including MongoDB, Snowflake, and Databricks.
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.
Leadership and mentoring experience.

Obowiązki

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 tools, technologies, and AI solutions to meet 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.

Benefity

Language classes.
Sponsored training and conferences.
Team-building events and an integration budget.
Medical and sports packages, eye care, and well-being support, including psychotherapy and coaching.
Full work equipment, including a laptop and other necessary devices.
A dedicated onboarding buddy.

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