About Us:

At SFL, we are transforming India's youth sports academy ecosystem using technology, data, and strategic investments. Our goal is to empower academies with advanced AI tools, analytics, and operational support.

Position Overview:

We are looking for an Machine Learning Engineer to lead the development of our performance and learning tools. This is an individual contributor role where you will design, build, and fine-tune Machine Learning models for player analytics, skill assessment, and automated highlight generation.

We want someone who is passionate about sports and excited to create solutions that bring together computer vision, machine learning, and sports science. You will work closely with our product and engineering teams to turn these ideas into real products and take them to production.

Role & Responsibilities:

Computer Vision & ML Models:

Use computer vision and machine learning techniques to extract meaningful insights from sports videos and match data.

MLOps:

Build and maintain the end-to-end sports analytics ML platform – from video ingestion to production on AWS using best MLOps practices.

Collaboration:

Work with the product and tech teams to align on features and integration plans while independently owning AI product delivery.

Continuous Improvement:

Monitor model performance, gather feedback, and refine algorithms to improve accuracy and user experience.

Data Management:

Process and analyse structured and unstructured data including videos, scores, and stats to improve model accuracy.

Ownership:

High ownership in a fast-paced start-up.

Basic Qualifications:

Bachelor's degree in Computer Science or a related field.
Strong problem-solving skills and a growth mindset.
Hands-on experience in Python with OpenCV, Object Detection models, Object Tracking, PyTorch/TensorFlow and other ML libraries.
2–4 years of experience in training and deploying computer vision models in production.
Practical experience working with AWS.
Effective use of AI tools (Copilot, Cursor, Claude, ChatGPT etc.) to accelerate development and research workflows.

Preferred Qualification:

Strong academic background with a degree from IITs, NITs, IIITs, BITS Pilani, or other top-tier institutions.
Knowledge of transformers, object detection models, Object Tracking and video analysis models.
Expertise in Docker, MLFlow, AWS services such as MediaConvert and Sagemaker.
Experience working in a large-scale consumer tech company.

Perks and Benefits:

Competitive salary and performance-linked incentives.
High ownership in building a greenfield AI product from scratch.

Sports For Life (SFL) is an Equal Opportunity Employer and is committed to conduct an objective recruitment process based on the requirements and merit of the candidates. It is against the policy to reject any candidate based on their gender, caste, race, sex, disability, colour, religion, creed or sexual orientation.

SFL has a zero-tolerance policy against any form of child abuse and harassment.

Machine Learning Engineer (Computer Vision)

Machine Learning Engineer - Computer Vision & LLM