Data Scientist / ML Engineer

12.6k - 19.3k PLN12 600 - 19 320 PLN/ mies./ mies.B2BB2B (netto)

MidZdalnie·WarszawaFull-time·B2B

#479430·Dodano 2 dni temu·1

Źródło: nofluffjobs.com

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Tech Stack / Keywords

Machine LearningData scienceAIPythonCloudGenAI LLM TensorFlow Kubernetes MLflow CI/CD AWS PyTorch DockerRAGLangChainLlamaIndexOpenAIHuggingfaceAzureMLOpsComputer vision

Podsumowanie oferty

As a Data Scientist / ML Engineer, you will develop and deploy machine-learning and AI solutions across client projects. Projects include an AI-powered industrial engineering platform that uses LLMs to turn technical documents into a knowledge graph, as well as automotive data solutions and tools for software engineering.

Wymagania

At least 3 years of commercial experience designing and implementing scalable AI solutions, including Machine Learning, predictive modeling, optimization, NLP, computer vision, or GenAI.
Experience developing ML algorithms from scratch through production deployment.
Strong Python programming skills, including clean code and object-oriented design.
Extensive knowledge of ML libraries, including Scikit-Learn, PyTorch, and TensorFlow.
Experience 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 client interaction.
Working experience with SQL and NoSQL databases, including MongoDB, Snowflake, or Databricks.
Knowledge of CI/CD principles and experience with GitHub and GitHub Actions.
Familiarity with MLOps, Kubernetes, and Docker.
Bachelor’s or master’s degree in Computer Science, Data Science, Mathematics, Physics, or a related field.

Nice to have:

Experience with Spark, Hadoop, or Kafka.
Practical experience with frontend frameworks such as React, Node.js, Nest.js, or TypeScript.

Obowiązki

Develop, implement, and validate Machine Learning solutions for project requirements.
Translate clients’ business problems into data science problems.
Design scalable AI solution architectures.
Develop data pipelines and workflows, ensuring data quality and security.
Collaborate with Data Engineering and Software Engineering teams to build and deploy AI applications.
Present findings and recommendations to stakeholders.
Plan tasks within an Agile/Scrum framework.
Build a backend system using LLMs to transform technical documents into a structured knowledge graph.
Develop an automotive data solution that processes and analyzes documents, extracts information, identifies relationships between data sources, and integrates with client infrastructure.
Build a system to analyze source-code repositories, create grammatical rules for unknown programming languages, and generate training content from those rules.

Benefity

Private healthcare.
Multisport card / sport subscription.
Referral bonus.
MyBenefit cafeteria.
Paid leave.
Training budget.
Language classes.
Team-building events.
Flexible working hours.
In-house training.
Free coffee.
Shower.

Opieka zdrowotna

Karta sportowa

Premie

Płatny urlop

Dofinansowanie szkoleń

Kursy językowe

Spotkania integracyjne

Elastyczne godziny

Szkolenia wewnętrzne

Napoje w biurze

Prysznic

Addepto

70 aktywnych ofert

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