Informacje o stanowisku

technologies-expected :

• Python
• NLP
• Computer Vision
• LLM
• Generative AI
• Machine Learning
• AI
• Cloud
• Technical leadership

• Big Data

• As a Lead Data Scientist / ML Engineer, you will have the exciting opportunity to work with a team of technology experts on challenging projects across various industries, leveraging cutting-edge technologies. Here are some of the projects we are seeking talented individuals to join:
• AI optimization engine for airport operation management. This project involves creating an AI-driven optimization engine to streamline airport operations, using real-time data from sources like radar, air traffic, and passenger information.
• AI recommendation engine for the leading innovation company. This project involves creation of AWS-powered solutions to provide domain-specific recommendations by employing sophisticated LLMs.

• 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 AL 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.

• 6+ years of commercial experience in designing and implementing scalable AI solutions (Machine Learning, Predictive Modeling, Optimization, NLP, Computer Vision, GenAI).
• Experience in Machine Learning projects leadership and team mentoring.
• 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 (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.

• 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.
• Choose from various employment options: B2B, employment contracts, or contracts of mandate.
• Make use of 20 fully paid days off available for B2B contractors and individuals under contracts of mandate.
• 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.

• sharing the costs of sports activities
• private medical care
• sharing the costs of foreign language classes
• sharing the costs of professional training & courses
• remote work opportunities
• fruits
• integration events
• no dress code
• video games at work
• coffee / tea
• drinks
• parking space for employees
• birthday celebration
• employee referral program
• dofinansowanie do okularów korekcyjnych

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