AI Engineer — Sports Analytics

🏆 We're Hiring | AI Engineer — Sports Analytics

📍 Remote | 🕐 Full-time | 🏢 Future Sportler | ₹7 LPA + ₹5 Lakh ESOPs

Sports is being redefined by AI — and we're the ones doing it. We're looking for an AI Engineer who wants to build systems that analyse games, understand athletes, and create experiences that fans have never seen before. If you've worked on Computer Vision or Voice AI and love sports — this is your dream role.

🛠️ What You'll Do:

• Build computer vision pipelines that analyse live and recorded sports footage — player detection, pose estimation, action recognition, and movement tracking
• Develop real-time video understanding systems for match analysis, highlight generation, and performance insights
• Create voice AI features — sports commentary assistants, voice-based fan engagement, or speech-driven analytics
• Train and fine-tune vision and audio models on sports-specific datasets
• Take AI features from prototype to production — optimized, monitored, and continuously improving
• Work closely with product and engineering teams to ship AI features users actually experience
• Explore and integrate cutting-edge research into real sports use cases

✅ What We're Looking For:

• 2+ years of hands-on experience in Computer Vision or Voice AI — shipped to production
• Strong proficiency in Python and deep learning frameworks — PyTorch or TensorFlow
• Experience with vision models and architectures — YOLO, ViT, SAM, ResNet, or similar
• Solid understanding of video analytics — frame extraction, temporal modelling, or optical flow
• Experience deploying and serving models in production — ONNX, TensorRT, or cloud-based inference
• Bonus if you've worked on speech/audio models — Whisper, TTS systems, or voice pipelines
• Strong debugging mindset — you fix models that break in the real world, not just on benchmarks
• Genuine interest or passion for sports — you understand the game, not just the data

🎯 Nice to Have:

• Experience with sports-specific CV — ball tracking, player identification, or event detection
• Familiarity with multimodal models combining vision, audio, and language (CLIP, LLaVA, Gemini)
• Experience with edge or on-device inference for real-time sports scenarios
• Knowledge of sports data formats, broadcast pipelines, or wearable sensor data
• Open-source contributions, Kaggle rankings, or published research in CV or audio AI

🎁 What We Offer:

• ₹7 LPA fixed + ₹5 Lakh in ESOPs — real equity in a growing sports tech company
• Ownership of AI systems that directly power live sports experiences
• Hard, meaningful problems — player tracking, game intelligence, fan engagement
• Work at the intersection of AI and Sports — one of the most exciting spaces right now
• Flexible, async-friendly work culture with a fast-moving team

📩 Apply: Send your resume, GitHub, or anything that shows your work to [email protected]