Senior Data Scientist / ML Engineer

Our requirements

• Proven commercial experience (6+ years) designing and implementing scalable AI solutions (Machine Learning, Predictive Modeling, Optimization, LLM, NLP, Computer Vision, GenAI).
• 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.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Physics, or a related field.

Optional

• Experience with Big Data technologies like Spark, Databricks, Hadoop, and Kafka is a plus.
• Leadership and/or mentoring experience is highly desirable.

Your 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.

About the project

This is how we organize our work

What we offer

• Work in a supportive team of passionate enthusiasts of AI & Big Data.
• Engage with top-tier global enterprises and cutting-edge startups on international projects.
• Enjoy flexible work arrangements, allowing you to work remotely or from modern offices and coworking spaces.
• Accelerate your professional growth through career paths, knowledge-sharing initiatives, language classes, and sponsored training or conferences, including partnerships with Databricks and Anthropic, which offer industry-leading training materials and certifications.
• Participate in team-building events and utilize the integration budget.
• Celebrate work anniversaries, birthdays, and milestones.
• Access medical and sports packages, eye care, and well-being support services, including psychotherapy and coaching.
• Get full work equipment for optimal productivity, including a laptop and other necessary devices.
• With our backing, you can boost your personal brand by speaking at conferences, writing for our blog, or participating in meetups.
• Experience a smooth onboarding with a dedicated buddy, and start your journey in our friendly, supportive, and autonomous culture.

Development opportunities we offer

• assistance in preparation to public speeches
• conferences abroad
• conferences in Poland
• development budget
• external training
• industry-specific e-learning platforms
• intracompany training
• soft skills training
• substantive support from technological leaders
• support of IT events
• technical knowledge exchange within the company
• time for development of your ideas

Benefits

• sharing the costs of sports activities
• private medical care
• sharing the costs of professional training & courses
• remote work opportunities
• flexible working time
• integration events
• no dress code
• video games at work
• coffee / tea
• drinks
• christmas gifts
• birthday celebration
• employee referral program
• Reimbursement for prescription glasses or contact lenses

Recruitment stages

• 1.
  Let's get to know each other (45 min)
• 2.
  Technical Interview (1h)
• 3.
  Management Interview (1h)

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