Senior Engineering Manager - Machine Learning

Super; Amsterdam; On-site; EUR 80,000 - 120,000; Full time

Job summary

Super is seeking a Senior Engineering Manager for Applied Machine Learning & Research in Amsterdam. This role involves leading technical contributions, project management, and mentoring a team of data scientists and ML engineers to develop innovative machine-learning solutions.

The ideal candidate possesses a Master’s or Ph.D., significant experience in machine learning and data science, and strong programming skills in Python. Join us to revolutionize the online gambling and sports-betting experience!

Qualifications

• 4+ years of machine-learning and data-science experience.
• 5+ years in leading engineering teams.
• Experience with training large-scale foundation models.

Responsibilities

• Design, develop, and deploy advanced machine-learning models.
• Manage and prioritize machine-learning projects.
• Lead and mentor a team of data scientists and ML engineers.

Skills

Machine learning

Data science

Python programming

Deep learning frameworks

Cloud computing (AWS)

Docker

Kubernetes

Problem-solving

Communication

Education

Master’s or Ph.D. in Computer Science or related field

Tools

TensorFlow

PyTorch

JAX

Spark

Snowflake

MLFlow

Airflow

Job description

About the Role

We’re looking for a hands‑on and motivated Senior Engineering Manager for Applied Machine Learning & Research to support the development and delivery of machine‑learning systems at Super Technologies. The team harnesses data to revolutionize the online gambling and sports‑betting experience, transforming complex data into actionable insights that enhance customer engagement, trust, and satisfaction. In this role you will split your time between technical contribution, project coordination, and people management – helping your team succeed while staying close to the code.

Qualifications

• Master’s or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field
• Proven experience (4 + years) in machine‑learning and data‑science roles
• Proven experience (5 + years) in leading or managing engineering teams, supporting the growth and performance of engineers
• Strong programming skills in Python and experience with deep‑learning frameworks such as TensorFlow, PyTorch, or JAX
• Experience with cloud computing platforms primarily AWS and containerisation technologies (e.g., Docker, Kubernetes)
• Excellent problem‑solving skills and the ability to work independently and collaboratively
• Strong communication and interpersonal skills

Preferred Qualifications

• Experience in the gaming or entertainment industry
• Experience with tools and technologies such as Spark, Snowflake, Qwak, MLFlow, Airflow, etc.
• Contributions to open‑source AI/ML projects or participation in AI/ML competitions (e.g., Kaggle)
• Experience with training and fine‑tuning large‑scale foundation models (e.g., GPT, BERT, T5) for various tasks
• Publications in top AI conferences, such as AAAI, IJCAI, NeurIPS, ICML, ICLR

Responsibilities

• Technical Expertise
  • Design, develop, and deploy advanced machine‑learning models to solve complex business problems
  • Stay updated with the latest trends and advancements in machine‑learning and AI technologies
  • Conduct code reviews and ensure best practices in model development and deployment
• Project Management
  • Manage and prioritise machine‑learning projects to align with business goals and objectives
  • Ensure timely delivery of high‑quality machine‑learning solutions
  • Coordinate with cross‑functional teams to integrate machine‑learning models into production systems
• People Management
  • Lead and mentor a team of 4‑5 data scientists and ML engineers, providing guidance and support in their day‑to‑day activities
  • Oversee the execution, development, growth, and performance of the ML team
  • Foster a collaborative and innovative team environment while building strong partnerships with product management and stakeholders

Equal Opportunity & Diversity

We hire and grow talent based on ability and potential, regardless of background and identity because we believe diverse perspectives drive better performance.