Software Engineer, AI/Computer Vision and LLMs

Are you passionate about building innovative solutions with the latest advancements in computer vision and multi-modal Large Language ModelsDo you want to contribute to industry-defining software and grow your skills at the cutting edge of AI research and applicationAt Nielsen Sports, we provide the most comprehensive and trusted data and analytics for the global sports ecosystem, helping clients understand media value, fan behavior, and sponsorship effectiveness. In this role, you will be a key contributor to our mission, developing and implementing AI systems that unlock novel insights from complex multimedia sports data. We are looking for enthusiastic Software Engineers at various levels (MTS-1 to MTS-3) to join our dynamic team.

• AI/ML System Development: Contribute to the design, development, and implementation of scalable AI/ML systems, with a focus on computer vision and LLM applications for sports media analysis.
• Model Implementation Training: Develop, train, test, and fine-tune deep learning models (eg, object detectors like RT-DETR, custom classifiers) on large-scale, domain-specific datasets under the guidance of senior engineers.
• Computer Vision Solutions: Implement computer vision algorithms and models to identify visual elements (eg, logos, brand assets) in sports content.
• LLM GenAI Application: Assist in exploring and implementing solutions leveraging LLMs and Generative AI for tasks such as data processing, feature extraction, and supporting model validation.
• Software Development Deployment: Write high-quality, maintainable code for AI/ML pipelines. Contribute to building APIs and integrating models into Nielsen Sports platforms.
• UI/UX for AI Tools: Develop or assist in developing internal tools and simple user interfaces (using frameworks like Streamlit, Gradio, or web stacks) to showcase model capabilities and support data workflows.
• Learning Innovation: Actively learn about advancements in computer vision, LLMs, and related AI fields. Contribute to evaluating and prototyping new technologies and methodologies.
• Collaboration: Work closely and collaboratively with senior engineers, data scientists, product managers, and other team members in an agile environment.
• Code Quality Optimization: Write efficient code and assist in optimizing model performance and resource utilization.
• Data Handling: Participate in data collection, preprocessing, and augmentation efforts to support model development.

Required Qualifications:

• Bachelor s or Master s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• 1-6 years of hands-on software development experience, with a keen interest or experience in AI/ML and Computer Vision.
• Experience with training or implementing deep learning models (eg, for object detection, classification) using common frameworks.
• Proficiency in Python and experience with deep learning frameworks such as PyTorch (preferred) or TensorFlow/Keras.
• Exposure to or interest in Large Language Models (LLMs) and their applications.
• Familiarity with developing simple UIs or scripting for model interaction or data tasks.
• Understanding of basic MLOps principles and familiarity with tools for model development and deployment (eg, Docker, Git).
• Solid software engineering fundamentals, including data structures, algorithms, code versioning (Git), and testing practices.
• Good problem-solving skills and an eagerness to learn and tackle new challenges.
• Strong communication and teamwork skills.
• Nice to have: Full Stack Development experience in any one stack
  

• Experience with Generative AI vision models.
• Contributions to open-source projects or personal AI/ML projects.
• Interest in or experience with sports data (broadcast feeds, social media imagery, sponsorship analytics).
• Familiarity with cloud computing platforms (AWS, GCP, Azure).
• Experience with video processing basics.
• Exposure to data pipeline tools.
• Ability to quickly learn new technologies and adapt to a fast-paced environment.