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Senior Machine Learning Engineer

1 month ago


Gurgaon, Haryana, India Zupee Full time

About Zupee

We are the biggest online gaming company with largest market share in Indian gaming sector's largest segment — Casual & Boardgame. We make skill-based games that spark joy in everyday lives of people by engaging, entertaining, and enabling earning while at play.

In three plus years of existence, Zupee has been on a mission to improve people's lives by boosting their learning ability, skills, and cognitive aptitude through scientifically designed gaming experiences. Zupee presents a timeout from stressful environments we live in today and sparks joy in lives of people through its games.

Zupee invests in people and bets on creating excellent user experiences to drive phenomenal growth. We have been running profitable at EBT level since 2020 while closing Series B funding at $102 million, at a valuation of $600 million. Zupee is all set to transform from a fast-growing startup to a firm contender for the biggest gaming studio in India.

Job Summary

This role involves developing end-to-end Deep Learning and GAN based models, leading and driving the deployment, life cycle management and monitoring of Machine Learning (ML) and Deep Learning (DL) models, and collaborating with Data Scientists, Data Engineers and application engineers to create and implement policies and governance for ML model life cycle.

About the Job

Role: Senior Machine Learning Engineer

Reports to: Manager- Data Scientist

Location: Gurgaon

Responsibilities:

  • Build end to end Deep Learning and GAN based models.
  • Lead and drive the deployment, life cycle management and monitoring of Machine Learning (ML) and Deep Learning (DL) models in all stages leading to production.
  • Provision and configure secure high-performance computing environments (clusters, storage, APIgateways etc ) to support hosting of ML/DL models at scale.
  • Collaborate with Data Scientists, Data Engineers and application engineers to create and implement policies and governance for ML model life cycle.
  • Running tests, interpreting test results, performance tuning and scaling.
  • Deployment and monitoring of real time ML applications.

Qualifications:

3+ years of experience with ML infrastructure and ML DevOps and Generative AI

  • Well versed with DL, GAN and LLM concepts.
  • 3+ years of overall engineering experience in distributed systems and data infrastructure
  • 3+ years experience coding in Python (preferred) or other languages like Java, nodeJS etc.
  • Experience working with ML engineers to build tooling and automation to support the entire ML engineering lifecycle, from experimentation to production operations.
  • Experience with Kafka, Docker, Kubernetes and ML CI/CD workflows
  • 3+ years experience with AWS or other public cloud platforms (GCP, Azure, etc.)
  • Excellent verbal and written communication skills.