Job Description
At Nielsen, we are passionate about powering a better media future for all by providing impactful insights that influence client decisions and deliver exceptional results. Our global team is dedicated to capturing audience engagement with content across various platforms and devices, standing at the forefront of the media revolution.
About Nielsen Sports
Nielsen Sports offers comprehensive data and analytics for the global sports ecosystem, enabling clients to understand media value, fan behavior, and sponsorship effectiveness. Our mission involves developing advanced AI systems to extract insights from multimedia sports data.
Position: Principal / Senior Principal AI Engineer
Key Responsibilities
- Technical Leadership & Architecture: Design scalable AI/ML systems, focusing on computer vision and LLM applications for sports media analysis.
- Model Development & Training: Develop and fine-tune deep learning models like RT-DETR, classifiers, and generative models on large datasets.
- Generalized Object Detection: Build models to identify logos, graphics, and other visual elements in sports content.
- LLM & GenAI Integration: Use LLMs and Generative AI for summarization, insight generation, and data validation.
- System Implementation & Deployment: Develop production pipelines, APIs, and integrate models into existing platforms.
- UI/UX for AI Tools: Create interfaces for showcasing models and facilitating data annotation.
- Research & Innovation: Keep updated with the latest in AI, experimenting with new methodologies.
- Mentorship & Collaboration: Guide junior engineers and work with cross-functional teams.
- Performance Optimization: Enhance model speed and accuracy, optimize hardware utilization.
- Data Strategy: Manage data acquisition, preprocessing, and augmentation.
Qualifications
- BSc/MSc/PhD in Computer Science, AI, ML or related field
- 5+ years (Principal), 8+ years (Senior) in AI/ML, focused on Computer Vision
- Experience with training object detection models (YOLO, Faster R-CNN, DETR)
- Proficiency with training LLMs (Llama 2/3, Mistral) using libraries like Hugging Face
- Strong Python skills, PyTorch or TensorFlow expertise
- Experience with Multi-Modal LLMs and transformer architectures
- UI development experience for AI tools
- Knowledge of MLOps practices and tools like Docker, Kubernetes, MLflow
- Solid software engineering skills, version control, testing, CI/CD
- Strong problem-solving and communication skills
- Full Stack Development experience
Preferred Skills
- Experience with Generative AI vision models
- Publications in top-tier AI/ML/CV conferences
- Sports data experience
- Cloud platform experience (AWS, GCP, Azure)
- Video processing expertise
- Familiarity with large data pipelines and distributed systems
- Proven project leadership and mentorship skills
Important Note
Candidates should be vigilant about scam communications; official Nielsen contacts will use verified channels during recruitment.