Lead Data Scientist / ML Engineer

July 27

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Big Data, Machine Learning, Data Science, AI, MLOps and DataOps Services

Data Science • Business Intelligence • Data Warehousing • Machine Learning • Artificial Intelligence

51 - 200

Description

• 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.

Requirements

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

Benefits

• 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. • Experience a smooth onboarding with a dedicated buddy, and start your journey in our friendly, supportive, and autonomous culture.