Senior Machine Learning Engineer

Key responsibilities:

Possess deep knowledge of core systems and take full responsibility for the code, design, and project delivery, ensuring high quality and on-time completion

Build and evolve end-to-end ML lifecycle systems from data processing to model serving — for journey prediction, churn/conversion propensity, and intervention-matching models — using technologies spanning big data frameworks to ML platforms (TensorFlow, PyTorch)

Design and implement sophisticated monitoring systems that track both technical health and model quality metrics (prediction accuracy, drift, intervention lift)

Create advanced experimentation frameworks that enable rapid A/B testing of journey-prediction algorithms and intervention strategies

Design and develop low-latency, high-throughput serving systems with appropriate caching strategies to support real-time intervention decisions

Establish MLOps best practices using MLflow for experiment tracking, model versioning, and deployment automation

Build stream processing pipelines for real-time feature computation on subscriber behavior and lifecycle signals that power dynamic journey personalization and next-best-action decisioning

Scale and optimize training and serving of machine learning models, including specialized solutions for embedding scaling

Collaborate with Product Managers and cross-functional teams to understand requirements and deploy high-quality software solutions that meet business objectives

SKILLS & ATTRIBUTES FOR SUCCESS:

Strong coding skills in Python, Java, Golang, or Scala

Experience with Big Data frameworks like Spark and Kubernetes for data and ML workloads

Proficient in implementing API performance monitoring solutions using tools such as Grafana, Prometheus, and Cloudwatch

Experience with machine learning libraries including TensorFlow, PyTorch, JAX or Keras

Skilled in developing end-to-end machine learning pipelines ensuring consistency between development and production environments

Ability to design scalable ML architectures tailored to site traffic and feature complexity for predictive algorithms

Familiar with model and data versioning, resource allocation and scaling, and logging to build optimal systems

Experienced in creating systems that monitor and react to faults in resources, data streams, and model responses

Expertise with MLOps tools for scalable, production-level deployment, including feature stores, model hosting and versioning, data versioning, prediction and drift monitoring, and automated remediation

Strong problem-solving skills and the ability to work effectively in a fast-paced environment

Commitment to continuous learning and professional development

PREFERRED EDUCATION & EXPERIENCE:

B.Tech/B.E/ Masters or equivalent degree. At least 4+ years of professional experience in software engineering roles, with a track record of delivering high-quality projects independently.

ABOUT US:

JioStar is a leading media & entertainment company in India that reaches over 700 million viewers a month in nine different languages. Our entertainment portfolio which cuts across general entertainment, movies, sports, infotainment, kids, and lifestyle content generates over 20,000 hours of original content every year.

JioStar, India’s leading streaming platform, enables us to reach and entertain audiences anywhere, anytime. JioStar has changed the way Indians consume their entertainment - from their favourite TV shows and movies to sporting extravaganzas.

Join us, and let's continue to inspire a billion imaginations.