ML Engineering Team Lead

WSC Sports, the pioneer in AI-powered sports content technology, empowers their clients world-wide to connect with their fans through AI-tailored sports content experiences. WSC Sports’ platform automates the creation, management and distribution of content, enabling sports rights holders to expand reach, grow fan bases, and unlock revenue opportunities across digital platforms.

Why WSC Sports:

You’ll work in an awesome environment alongside some of the most innovative people in the industry, using cutting-edge technologies and tools (video editing, Gen AI, data, etc.). At WSC Sports, you have the opportunity to directly influence the products and tools used by our clients, including sports giants such as the NBA, Bundesliga, LaLiga, ESPN - and that’s just the beginning of what WSC Sports has to offer! Join us and be a part of the best team in tech as we Fuel the Fandom worldwide.

As a ML Engineering Team Lead at WSC Sports, you will lead a multidisciplinary team of algorithm and software engineers responsible for designing, building, and operating the next-generation content creation engine. The team focuses on leveraging agentic systems and advanced ML technologies to orchestrate complex, end-to-end production workflows at scale.

In this role, you will translate high-level product and business goals into robust, production-ready solutions, working hands-on across the full lifecycle - from research and system design to deployment, monitoring, and continuous improvement. You will collaborate closely with Product, Platform, Data, and other R&D teams in a fast-paced, agile environment, ensuring that algorithms and software are seamlessly integrated into real-world, high-throughput systems.

You will combine technical leadership, architectural thinking, and people leadership to drive innovation, execution, and delivery, while shaping how intelligent, automated content is created and scaled across WSC Sports’ products.

What you’ll do:

• Lead and mentor a multidisciplinary team of algorithm and software engineers, fostering ownership, technical excellence, and professional growth.
• Own the delivery of complex, end-to-end systems for automated content creation, from early design and experimentation through production deployment, monitoring, and iteration.
• Drive the design and orchestration of agentic systems, working hands-on with the team to integrate ML models, business logic, and software infrastructure across research, engineering, and production at scale.
• Translate product and business challenges into technical solutions, defining system architecture, prioritizing initiatives, and guiding execution in an agile environment.
• Ensure production readiness and reliability, overseeing deployment, monitoring, performance, and continuous improvement of algorithms and services in a live environment.
• Collaborate closely with Product, Platform, Data, and other R&D teams, aligning technical execution with product strategy and business goals in a multidisciplinary setting.
• Continuously evolve technically and professionally, encouraging knowledge sharing, joint problem-solving, and awareness of emerging trends in ML, agentic systems, and large-scale software architectures.

Requirements

What you’ll need:

• B.Sc. or M.Sc. in Computer Science, Electrical Engineering, or a related field, with a focus on AI / NLP / Computer Vision / Machine Learning from a well-known university (M.Sc. preferred).
• Proven experience leading and managing a technical team (minimum 3 engineers), with a strong ability to mentor, guide, and scale people in a fast-paced environment.
• Strong background in applied ML and algorithms, with hands-on experience delivering production-grade systems.
• Experience with Generative AI and LLMs, including integration into multi-component workflows.
• Proven end-to-end ownership: from problem definition and design to deployment and operation at scale.
• Broad technical expertise across ML, algorithms, and software engineering to design scalable and maintainable architectures.
• Experience in high-scale, production environments, ensuring reliability, performance, and maintainability.
• Excellent communication and collaboration skills across Product, Engineering, Data, and business teams.