Manager AI/ML

Nasze wymagania: Education: Advanced degree in Data Science, Machine Learning, Computer Science, Statistics, or a related field; PhD preferred. Experience: Minimum 12 years of experience in data science & machine learning, with at least 3 years in a leadership role (managing teams) and proven ability to lead and collaborate with distributed and remote teams. Experience deploying ML models in production environments at scale. Developed scalable ML systems and architectures that support model reusability across multiple customers with minimal or no customization. Expertise in programming languages (Python, R, SQL), machine learning frameworks (TensorFlow, PyTorch, Scikit-learn), MLOps tools (MLflow, Kubeflow, SageMaker), and any AutoML platforms (Google AutoML, H2O.ai, Azure AutoML). Knowledge of data engineering, data pipelines and data lake/, data lakehouse and data mesh architecture. Proficient in Python for model development and data manipulation. Mile widziane: Experience with Spark and Mage AI is a plus. Experience with LLMs, generative AI including productionalizing chatbots is a plus. Background in software engineering or DevOps is a strong advantage. Previous domain experience in Supply Chain, Pricing , Inventory and Service Fulfilment. O projekcie: We are seeking a Manager/Senior Manager AI& ML to lead a high-impact team of data scientists, ML engineers, and AI specialists in building cutting-edge AI/ML solutions. This role requires a blend of technical expertise in DS, AI/ML, MLOps, with strong leadership capabilities. The ideal candidate will have a proven track record of deploying scalable AI/ML systems and fostering a high-performing, innovative team culture. Zakres obowiązków: Strategic Leadership: Develop and execute the organization's data science strategy, with a strong focus on advancing machine learning, MLOps, and AutoML practices to optimize operational workflows and model lifecycle management. Team Management: Lead, mentor, and grow a dynamic team of data scientists, ML engineers and specialists, fostering a collaborative and innovative work environment. Define and evolve the long-term AI/ML architecture roadmap, ensuring scalability, maintainability, and integration with existing systems. Data Strategy: Define and implement a roadmap for data collection, storage, and analysis, emphasizing the integration of machine learning pipelines, scalable MLOps frameworks, and AutoML systems for accelerated model development. Advanced Analytics: Oversee the deployment of predictive models, machine learning algorithms, and statistical analyses, ensuring the seamless integration of AutoML platforms for enhanced efficiency and scalability. Model Lifecycle Enhancement: Focus on improving model lifecycle time and scalability by implementing cutting-edge practices in MLOps and AutoML to reduce time-to-market and ensure robust, adaptable solutions. Oferujemy: Environment facilitating professional growth 🚀 Respectful and friendly work environment. Internal training sessions, external conferences and training options. Free English & Swedish classes. Fringe benefits (private medical care, multisport card, life insurance). Flexible model of work, working hours and no micromanagement. We do respect one another, and we do enjoy working together – we play pool and board games (mostly online these days), organize charity activities - to name just a few😊