Machine Learning (ML)This role is at Glance
What you will be doing
We are looking for a Data Scientist who can operate at the intersection of classical machine learning, large-scale recommendation systems, and modern agentic AI systems.
You will design, build, and deploy intelligent systems that power Glance’s personalized lock screen and live entertainment experiences. This role blends deep ML craftsmanship with forward-looking innovation in autonomous/agentic systems.
Your responsibilities will include:
Classical ML & Recommendation Systems
- Design and develop large-scale recommendation systems using advanced ML, statistical modeling, ranking algorithms, and deep learning.
- Build and operate machine learning models on diverse, high-volume data sources for personalization, prediction, and content understanding.
- Develop rapid experimentation workflows to validate hypotheses and measure real-world business impact.
- Own data preparation, model training, evaluation, and deployment pipelines in collaboration with engineering counterparts.
- Monitor ML model performance using statistical techniques; identify drifts, failure modes, and improvement opportunities.
Agentic Systems & Next-Gen AI
- Build and experiment with agentic AI systems that autonomously observe model performance, trigger experiments, tune hyperparameters, improve ranking policies, or orchestrate ML workflows with minimal human intervention.
- Apply LLMs, embeddings, retrieval-augmented architectures, and multimodal generative models for semantic understanding, content classification, and user preference modeling.
- Design intelligent agents that can automate repetitive decision-making tasks—e.g., candidate generation tuning, feature selection, or context-aware content curation.
- Explore reinforcement learning, contextual bandits, and self-improving systems to power next-generation personalization.
Cross-functional impact
- Collaborate with Designers, UX Researchers, Product Managers, and Software Engineers to integrate ML and GenAI-driven features into Glance’s consumer experiences.
- Contribute to Glance’s ML/AI thought leadership—blogs, case studies, internal tech talks, and industry conferences.
- Thrive in a multi-functional, highly collaborative team environment with engineering, product, business, and creative teams.
- Plus: Interface with stakeholders across Product, Business, Data, and Infrastructure to align ML initiatives with strategic priorities.
The experience we need
We are seeking candidates with deep expertise in ML, recommendation systems, and a strong appetite for building agentic AI systems.
You should have experience with:
- Large-scale ML and recommendation systems (collaborative filtering, ranking models, content-based approaches, embeddings).
- Classical ML and deep learning techniques across NLP, sequence modeling, RL, clustering, and time series.
- Experience in deploying ML workflows/models in production system
- Big data processing (Spark, distributed data systems) and cloud computing.
- Designing end-to-end ML solutions—from prototype to production.
- Plus: Building or experimenting with LLMs, generative models, and agentic AI workflows (e.g., autonomous evaluators, self-improving pipelines, automated experiment agents).
We value curiosity, problem-solving ability, and a strong bias toward experimentation and production impact.
Qualifications
- Bachelor’s/Master’s in Computer Science, Statistics, Mathematics, Electrical Engineering, Operations Research, Economics, Analytics, or related fields. PhD is a plus.
- 4+ years of industry experience in ML/Data Science, ideally in large-scale recommendation systems or personalization.
- Experience with LLMs, retrieval systems, generative models, or agentic/autonomous ML systems is highly desirable.
- Expertise with algorithms in NLP, Reinforcement Learning, Time Series, and Deep Learning, applied on real-world datasets.
- Proficient in Python and comfortable with statistical tools (R, NumPy, SciPy, PyTorch/TensorFlow, etc.).
- Strong experience with the big data ecosystem (Spark, Hadoop) and cloud platforms (Azure, AWS, GCP/Vertex AI).
- Comfortable working in cross-functional teams.
- Familiarity with privacy-preserving ML and identity-less ecosystems (especially on iOS and Android).
- Excellent communication skills with the ability to simplify complex technical concepts.
Shubham Vishwakarma
Full Stack Developer - Averlon
About InMobi
About
InMobi is a leading global consumer technology and advertising company redefining how businesses connect with mobile-first consumers and how people discover content, commerce, and experiences on their devices. Originally launched as a mobile search service, InMobi has since evolved into one of the world’s most advanced ad-tech platforms, combining cutting-edge AI, programmatic technology, and consumer insights to help brands, advertisers, and publishers grow and engage audiences at scale.
✨ Our most popular consumer brands are -
Glance - A consumer technology company and an unconsolidated subsidiary of InMobi Group. It operates an AI-driven lock-screen content and commerce platform that delivers personalized experiences, entertainment, news, and commerce directly to users’ lock screens. Glance also includes properties such as Roposo and Nostra under its umbrella. It was founded in 2019 and is backed by investors including Google, Jio Platforms, and Mithril Capital while being owned by InMobi.
1Weather - A weather forecasting app used globally that has been incorporated into InMobi’s offerings through strategic partnerships (notably delivering weather alerts via Glance lock screens in collaboration with the India Meteorological Department). The app is leveraged by InMobi’s ecosystem to power weather updates and real-time alerts, integrating with Glance’s lock-screen platform to bring actionable weather insights directly to users,
👥 Founders & Leadership
Founded in 2007 as mKhoj, InMobi was started by Naveen Tewari (Founder & CEO) along with co-founders Mohit Saxena, Amit Gupta, and Abhay Singhal. What began in a Bangalore apartment as an SMS-based service evolved into a global mobile advertising and consumer technology company. Today, InMobi’s leadership team includes seasoned executives driving growth across revenue, product, and technology worldwide.
💰 Funding & Financials
InMobi has raised $215M+ in equity funding since inception, including a landmark $200M Series C led by SoftBank in 2011. More recently, the company secured $100M in debt financing in 2024 and $350M in growth capital in late 2025, with discussions underway for a $400M Series E at an ~$8B valuation.
🏆 Milestones
- 2011: Achieved unicorn status with major investment from SoftBank; launched China operations.
- 2019: Launched Glance — a lock-screen content discovery platform, and acquired social video platform Roposo.
- 2020–22: Expanded product portfolio with AI-enabled solutions like InMobi Pulse, InMobi DSP, InMobi Telco, UnifID, and Meson mediation platform.
- 2024–25: Secured $100M AI-focused financing, explored a potential $400M Series E at ~$8B valuation, and raised $350M in growth funding ahead of IPO preparations.
- 2025: Founders bought back a major SoftBank stake, increasing founder ownership and positioning the company for a future public listing.
🌍 Global Footprint & Impact
With offices across Asia, Europe, and North America, InMobi’s platforms power advertising campaigns that reach over a billion devices globally, serving billions of impressions every month. It has become one of the world’s largest independent mobile ad networks, competing with major players while maintaining deep technology innovation in programmatic and AI-driven marketing
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