Lead Machine Learning Engineer

0 - 5 years

6 - 10 Lacs

Posted:1 day ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

What does the team do?


Serving recommendations to 300+ million users entails developing large scale personalization and recommendation models that understand user needs and preferences in realtime, while also helping creators grow their audiences on our platforms. A subset of the problems we tackle include:

  • Serving personalized feeds for 300+ million users via real-time candidate generators, multi-task prediction models, whole-page optimization, and in-session personalization.
  • Nurturing our content and creator ecosystem, and developing models for strategic content valuation.
  • Multi-objective balancing and long term measurement.

We rely extensively on state-of-the-art ML around personalization, deep learning, causal inference, optimization, ranking and recommendation.


AI - Our AI teams are spearheading the research and development, presenting innovations at various conferences. to learn.

Learn from our CEO Ankush about our culture, innovation and growth.


What Youll Do


Were hiring a Lead Machine Learning Engineer

within the

ShareChat AI team

to drive the development of

recall models

in our recommendation systems.
This is a

high-impact IC role

at the heart of our

Feed team

, with end-to-end ownership of ML modeling from

training and deployment

to

continuous improvement

of models that predict key user actions such as

clicks, installs, and transactions

.Youll also work on applying machine learning to

feed recommendations

for

short videos and episodic content

, where even small modeling improvements can create significant user and business impact.

At ShareChat, the pace of experimentation and iteration is fast, success rates are high, and the environment is deeply technical. Youll be joining us at a time when the

science and engineering behind large-scale recommendation systems

are evolving rapidly and youll be part of shaping what comes next.

Who You Are

  • You develop large-scale systems that serve recommendations to

    300M+ users

    .
  • You drive the

    ML roadmap

    for

    recall-oriented candidate generation systems

    .
  • You take

    end-to-end ownership

    of ML systems, from model formulation and experimentation to production deployment and monitoring.
  • You influence

    architectural design

    for complex ML systems that balance user satisfaction, scalability, and business goals.
  • You bring

    4+ years of experience

    in applied machine learning with a

    Bachelors, Masters, or PhD

    in Computer Science, Machine Learning, or a related field.

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