Job Summary

We're looking for a Senior Backend Software Development Engineer (SDE 3) with deep technical expertise in building and operating production systems at scale. You'll own entire components/services within microservices and data pipelines that handle ~200K queries per second and process petabytes of data daily. This role demands hands-on coding excellence, strong Low-Level Design (LLD) skills, and complete ownership—from component architecture through infrastructure management to cost optimization. You'll architect solutions, lead technical decisions, and drive operational excellence while shipping code daily.

Key Responsibilities:

• Component Ownership: Own one or more critical components/services end-to-end—responsible for architecture, development, deployment, operations, and evolution
• Technical Ownership: Own the entire lifecycle of your components—design, implementation, testing, deployment, monitoring, incident response, and continuous improvement
• Low-Level Design: Create detailed technical designs (LLD) for complex systems—defining data models, APIs, concurrency patterns, and failure modes
• Hands-on Development: Write production-grade code daily—this is not a purely architectural role; you'll be deep in the codebase
• Infrastructure Ownership: Own and operate the infrastructure your components run on—capacity planning, scaling, reliability improvements
• Cost Management: Drive cost optimization for owned components—analyze spending, identify waste, implement efficient architectures
• Scale & Performance: Build and optimize systems handling 200K+ QPS and petabyte-scale data processing
• Observability: Design and implement comprehensive monitoring, alerting, and debugging capabilities for owned components
• Incident Leadership: Lead incident response for your components and related services, conduct post-mortems, drive systemic improvements
• On-Call Excellence: Participate in on-call rotations and ensure your components are operationally sound (runbooks, alerts, dashboards)
• Technical Roadmap: Define and drive the technical roadmap for your owned components—balancing feature development, tech debt, and operational improvements
• Technical Mentorship: Guide junior and mid-level engineers on system design, code quality, and production best practices
• Cross-functional Collaboration: Work with product, infra, and other eng teams to define requirements and deliver solutions
• Agile Execution: Break down complex projects, deliver incrementally in daily cadence, iterate based on feedback

Required Qualifications:

• Experience: 4-5+ years building and operating backend systems in production environments at scale
• Education: B.E./B.Tech in Computer Science or equivalent practical experience
• Component Ownership: Proven track record of owning significant components or services from inception to maturity—demonstrable end-to-end ownership
• Low-Level Design (LLD): Proven ability to create detailed technical designs—data structures, algorithms, API contracts, concurrency models, failure handling
• Programming Mastery: Expert-level proficiency in at least one modern language (Go, Python, Java, etc.) with track record of writing maintainable, performant production code
• Databases: Deep hands-on experience with SQL and NoSQL databases—schema design, query optimization, indexing strategies, operational troubleshooting
• Microservices at Scale: Extensive experience building, deploying, and operating microservices handling high throughput and large data volumes
• Data Pipelines: Strong background designing and running data processing pipelines at scale (batch and/or streaming)
• Observability: Expert understanding of metrics, logging, tracing, and alerting—you know how to make systems debuggable
• Production Operations: Significant experience with incident response, on-call rotations, debugging live issues under pressure
• Infrastructure Knowledge: Hands-on experience managing infrastructure, understanding resource utilization, capacity planning
• Cost Consciousness: Experience analyzing and optimizing infrastructure costs at scale
• Distributed Systems: Strong fundamentals in distributed systems, concurrency, consistency models, and failure scenarios
• Accountability: Track record of taking full ownership—from design through deployment to ongoing operations and improvements

Preferred Qualifications:

• Experience with cloud platforms (GCP, AWS, or Azure) including cost management tools
• Kubernetes and container orchestration at scale
• Infrastructure as Code (Terraform, Pulumi, etc.)
• Streaming data systems (Kafka, Pub/Sub, Kinesis, Flink, etc.)
• SRE principles and reliability engineering practices
• Experience with FinOps or infrastructure cost optimization
• Performance profiling and optimization (CPU, memory, I/O)
• Technical leadership experience including mentorship of teams and driving multi-component initiatives
• Open source contributions or recognized technical writing

Glance - An InMobi Group Company    

Founded in 2019, Glance is a consumer technology company that operates some of the most disruptive digital platforms including Glance, Roposo, and Glance TV. Glance has redefined the way the internet is consumed on the lock screen, removing the need to search for and download apps. Over 400 million smartphones now come enabled with Glance’s next-generation internet experience.   
  
Roposo has revolutionized commerce by launching a destination for creator-led live entertainment commerce. Glance TV is changing the way consumers engage and interact with their televisions.   
  
Headquartered in Singapore, Glance is an unconsolidated subsidiary of InMobi Group and is funded by Jio Platforms, Google, and Mithril Capital. For more information, visit glance.com, roposo.com, and inmobi.com.   

What should you know about joining Glance?  

At Glance, we walk the talk – free yourself, dream big, and chase your passion! On joining, you’ll have opportunities to make an immediate impact on mission-critical projects, as you work with highly capable and ambitious peer groups.   

Be rewarded for your autonomy even as you collaborate. Ideate, innovate, and inspire by leveraging bleeding-edge tech to disrupt consumer experiences.   

While you work, we’ll take care of nourishing your body, mind, and soul. This includes daily meals, gym, trainings, tech tools, and regular unwind sessions. Also, feel free to bring your kids – even the furry ones – to the office!  

Role overview:

You will drive the vision and strategy for the Commerce Intelligence at Glance  such as Multi Modal Search, Recommendation Systems, Brand and Price Affinity Modeling and will play a transformational role in driving the larger AI-first aspirations of the company. The Commerce Intelligence team at Glance will play a critical role in driving commerce across the platform.

You will have knowledge of current AI and machine learning capabilities and advances in the field. You should also be interested in the academics of data science but be more focused on practical application within recommendation and personalization technology. You will be able to clearly articulate the purpose of data science solutions to key stakeholders and customers, and then translate those into action for the business. The solutions you and your teams provide will encompass such things as product innovations, create efficiencies and automation across the business, improve data architecture and system architecture, mitigate business risks, and create process improvements. 

We are searching for an individual who thrives on describing a vision and inspiring a team to achieve it. We need a leader who will remove obstacles, break barriers, empower, communicate, and engage. Someone who truly harnesses advanced analytic data modelling systems to drive positive outcomes for our customers. From the defining of a strategy to the execution of it, you will also develop, collect, and report the objective metrics required to assure it. You will own driving employee engagement and increasing productivity across the Data Science team and into Engineering.

The impact you’ll make:

• Define the overall vision for our commerce intelligence, focused on up-levelling internal use of machine learning.
• Provide technical leadership of overall architecture, ML approaches, performance monitoring, continuing improvement, and production deployments.
• Manage, develop, coach, and mentor a team of machine learning engineers and big data specialists.
• Partner with our business and product teams to help predict system behaviour, establish metrics, identify bugs, and improve debugging skills.
• Ensure data quality and integrity within our products as well as our teams.
• Partner with our client-facing teams and customers to enhance products and develop client solutions applying critical thinking skills to remove extraneous inputs.
• Conceive, plan, and prioritize data projects.
• Lead data mining and collection procedures, especially focused on unstructured and siloed data sets.
• Experiment with new models and techniques.
• Drive the implementation of models into Production through various Engineering teams
• Create a positive culture to maximize productivity and minimize attrition

The experience you'll need:

• PhD or Master’s in a quantitative field such as Computer Science, Electrical Engineering, Statistics, Mathematics, Operations Research or Economics, Analytics, Data Science. Or bachelor's with additional experience.

• 10+ years of ML related industry experience working on large-scale recommendation systems or personalization. With 3+ years in a leadership role.

• You would bring deep expertise in the applied algorithms, models, and techniques used to design, scale, and optimize large-scale recommendation systems.
• You should be comfortable with software programming and statistical platforms such as Tensorflow, PyTorch, scikit-learn, etc. etc.
• You should be comfortable with using one or more distributed training technologies such as Apache spark, RAPIDS, dask, etc. along with MLOps stack such as kubeflow, mlflow, or their cloud counterparts
• Comfortable collaborating with cross-functional teams.
• Excellent technical and business communication skills and should know how to present technical ideas in a simple manner to business counterparts.
• Possess a high degree of curiosity and ability to rapidly learn new subjects
• Experience in e-commerce is plus.

About the Role

As a GPU Systems Engineer, you’ll lead design and optimization efforts across our GPU inference stack.
You will architect the libraries and runtime systems that enable Stable Diffusion, multimodal transformers, and emerging video generation models to run efficiently at scale.

You’ll guide cross-functional teams, influence hardware selection, and set the technical vision for GPU optimization practices across the company.

Key Responsibilities

• Architect high-performance inference runtimes, kernel dispatchers, and memory planners for large diffusion and transformer workloads.
• Lead investigations into cross-GPU performance bottlenecks, communication overheads, and scheduling inefficiencies.
• Drive multi-GPU parallelism strategies — model, pipeline, and tensor parallelization.
• Establish company-wide GPU optimization standards, tooling, and SLIs.
• Collaborate with research to design scalable implementations of novel architectures.
• Mentor engineers in profiling, tuning, and low-level optimization.
• Partner with hardware vendors and infra teams to maximize cluster utilization.

Required Qualifications

• 5+ years in high-performance computing, GPU runtime systems, or ML infrastructure.
• Proven expertise in CUDA / Triton / C++, with deep understanding of GPU scheduling, occupancy, register usage, and tensor cores.
• Experience building and maintaining distributed inference or training systems.
• Ability to design abstractions balancing flexibility and performance.
• Strong knowledge of NCCL, NVLink, PCIe, and interconnects.
• Familiar with profiling automation and performance dashboards.
• Excellent technical leadership and mentoring capabilities.

Preferred Qualifications

• Background in compiler-aided optimization (TVM, XLA, MLIR, Triton).
• Experience tuning Stable Diffusion or transformer inference pipelines.
• Exposure to heterogeneous compute backends (AMD ROCm, TPU, ASICs).
• Experience working with hardware–software co-design initiatives.
• Open-source or research contributions in GPU optimization

Glance - An InMobi Group Company    

Founded in 2019, Glance is a consumer technology company that operates some of the most disruptive digital platforms including Glance, Roposo, and Glance TV. Glance has redefined the way the internet is consumed on the lock screen, removing the need to search for and download apps. Over 400 million smartphones now come enabled with Glance’s next-generation internet experience.   
  
Roposo has revolutionized commerce by launching a destination for creator-led live entertainment commerce. Glance TV is changing the way consumers engage and interact with their televisions.   
  
Headquartered in Singapore, Glance is an unconsolidated subsidiary of InMobi Group and is funded by Jio Platforms, Google, and Mithril Capital. For more information, visit glance.com, roposo.com, and inmobi.com.    

  
What should you know about joining Glance?  
 

At Glance, we walk the talk – free yourself, dream big, and chase your passion! On joining, you’ll have opportunities to make an immediate impact on mission-critical projects, as you work with highly capable and ambitious peer groups.   
  

Be rewarded for your autonomy even as you collaborate. Ideate, innovate, and inspire by leveraging bleeding-edge tech to disrupt consumer experiences.   
  

While you work, we’ll take care of nourishing your body, mind, and soul. This includes daily meals, gym, trainings, tech tools, and regular unwind sessions. Also, feel free to bring your kids – even the furry ones – to the office!  

Role overview:

You will drive the vision and strategy for the Recommendation Systems team at Glance and will play a transformational role in driving the larger AI-first aspirations of the company. Recommendations team at Glance plays key role for all Ad revenue – programmatic and direct – on all Glance user experiences. Revenue has been growing steadily, and we’re well placed to make the trajectory steeper. Expertise in designing, building, and operating large-scale recommendation systems is a must.

You will have knowledge of current AI and machine learning capabilities and advances in the field. You should also be interested in the academics of data science but be more focused on practical application within recommendation and personalization technology. You will be able to clearly articulate the purpose of data science solutions to key stakeholders and customers, and then translate those into action for the business. The solutions you and your teams provide will encompass such things as product innovations, create efficiencies and automation across the business, improve data architecture and system architecture, mitigate business risks, and create process improvements. 

We are searching for an individual who thrives on describing a vision and inspiring a team to achieve it. We need a leader who will remove obstacles, break barriers, empower, communicate, and engage. Someone who truly harnesses advanced analytic data modelling systems to drive positive outcomes for our customers. From the defining of a strategy to the execution of it, you will also develop, collect, and report the objective metrics required to assure it. You will own driving employee engagement and increasing productivity across the Data Science team and into Engineering.

The impact you’ll make:

• Define the overall vision for our recommendation applications, focused on up-levelling internal use of machine learning
• Provide technical leadership of overall architecture, ML approaches, performance monitoring, continuing improvement, and production deployments
• Manage, develop, coach, and mentor a team of machine learning engineers and big data specialists
• Partner with our business and product teams to help predict system behaviour, establish metrics, identify bugs, and improve debugging skills
• Ensure data quality and integrity within our products as well as our teams
• Partner with our client-facing teams and customers to enhance products and develop client solutions applying critical thinking skills to remove extraneous inputs
• Conceive, plan, and prioritize data projects
• Lead data mining and collection procedures, especially focused on unstructured and siloed data sets
• Experiment with new models and techniques.
• Drive the implementation of models into Production through various Engineering teams
• Create a positive culture to maximize productivity and minimize attrition

The experience you'll need:

• PhD or Master’s in a quantitative field such as Computer Science, Electrical Engineering, Statistics, Mathematics, Operations Research or Economics, Analytics, Data Science. Or Bachelor's with additional experience.
• 12+ years of ML related industry experience working on large-scale recommendation systems or personalization. With 5+ years in a leadership role.
• You would bring deep expertise in the applied algorithms, models, and techniques used to design, scale, and optimize large-scale recommendation systems.
• You should be comfortable with software programming and statistical platforms such as Tensorflow, PyTorch, scikit-learn, etc. etc.
• You should be comfortable with using one or more distributed training technologies such as Apache spark, RAPIDS, dask, etc. along with MLOps stack such as kubeflow, mlflow, or their cloud counterparts
• Comfortable collaborating with cross-functional teams.
• Excellent technical and business communication skills and should know how to present technical ideas in a simple manner to business counterparts.
• Possess a high degree of curiosity and ability to rapidly learn new subjects

Glance - An InMobi Group Company    

Founded in 2019, Glance is a consumer technology company that operates disruptive digital platforms including Glance, Roposo, and Nostra. Glance’s ’smart lock screen’ inspires consumers to make the most of every moment by surfacing relevant experiences without the need for searching and downloading apps. Glance Lock Screen is currently available on over 450 million smartphones worldwide. Roposo is a LIVE platform that is revolutionizing live experiences, through a unique, immersive, creator-led approach. Nostra is the largest gaming platform in India and Southeast Asia, offering gamers engaging ways to discover, play, watch, learn and compete.   
 
Headquartered in Singapore, Glance is an unconsolidated subsidiary of InMobi Group and is funded by Jio Platforms, Google, and Mithril Capital. For more information visit glance.com, nostra.gg, and roposo.com

What should you know about joining Glance?  

At Glance, we walk the talk – free yourself, dream big, and chase your passion! On joining, you’ll have opportunities to make an immediate impact on mission-critical projects, as you work with highly capable and ambitious peer groups.   

Be rewarded for your autonomy even as you collaborate. Ideate, innovate, and inspire by leveraging bleeding-edge tech to disrupt consumer experiences.   

While you work, we’ll take care of nourishing your body, mind, and soul. This includes daily meals, gym, trainings, tech tools, and regular unwind sessions. Also, feel free to bring your kids – even the furry ones – to the office!

What you will be doing?

Glance is looking for a Machine Learning Engineer.

As an ML engineer you will be responsible for contributing to the design, development, deployment, testing, maintenance and enhancement of ML software solutions. You will work closely with data scientists to collaborate and support the development of ML data pipelines, platforms and infrastructure.

Day-to-day activities include:

• architecting and implementing end-to-end solutions for accelerating experimentation and model building,

• creation of microservices and APIs for serving ML models and ML services,

• designing and implementing potential products and proof-of-concepts,

• working closely with engineering, product, and newsroom teams to define and deploy new ML / AI products,

• exploring and onboarding new platforms, technologies and algorithms,

• managing project priorities, deadlines and deliverables. We are looking for candidates with an enthusiasm for tackling audacious challenges, the ability to take ownership of end-to-end solutions, and a passion for elegance in deep problem solving. Preferred Qualifications:

• Five+ years' experience working in a ML Engineering role with proven track record of delivering high-impact ML solutions.

• Bachelor’s degree, Master’s or PhD in computer science, Mathematics, Statistics, or other analytical fields

• Demonstrated ability to own end-to-end project delivery while maintaining transparent communication

• Hands-on experience and strong theoretical understanding of Recommender Systems.

• Experience working with Python, Golang, Spark or other open-source software with data science libraries

• Strong experience in advanced math and statistics

• Excellence in technical documentation and project leadership, with proven ability to drive results independently with cross-functional teams

• Experience with being actively engaged in data science or other research-oriented position.

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.

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.
• 6+ 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.

Glance - An InMobi Group Company    

Founded in 2019, Glance is a consumer technology company that operates some of the most disruptive digital platforms including Glance, Roposo, and Glance TV. Glance has redefined the way the internet is consumed on the lock screen, removing the need to search for and download apps. Over 400 million smartphones now come enabled with Glance’s next-generation internet experience.   
  
Roposo has revolutionized commerce by launching a destination for creator-led live entertainment commerce. Glance TV is changing the way consumers engage and interact with their televisions.   
  
Headquartered in Singapore, Glance is an unconsolidated subsidiary of InMobi Group and is funded by Jio Platforms, Google, and Mithril Capital. For more information, visit glance.com, roposo.com, and inmobi.com.    

  
What should you know about joining Glance?  
 

At Glance, we walk the talk – free yourself, dream big, and chase your passion! On joining, you’ll have opportunities to make an immediate impact on mission-critical projects, as you work with highly capable and ambitious peer groups.   
  

Be rewarded for your autonomy even as you collaborate. Ideate, innovate, and inspire by leveraging bleeding-edge tech to disrupt consumer experiences.   
  

While you work, we’ll take care of nourishing your body, mind, and soul. This includes daily meals, gym, trainings, tech tools, and regular unwind sessions. Also, feel free to bring your kids – even the furry ones – to the office!  

We're building one of the most ambitious platforms in consumer AI — a multi-surface commerce ecosystem spanning lock-screen, mobile, and TV, powered by large-scale GenAI, multimodal inference, and real-time distributed systems.

If you love designing systems that millions interact with daily — often without realizing the engineering magic underneath — this is your playground.

WHAT YOU WILL DO

Architect & Build for Massive Scale

- Own end-to-end design of core platform components at 100K+ QPS, serving tens of millions of users

- Drive innovations across distributed compute, storage, consistency, and failure handling

- Build infrastructure powering:

→ GPU-efficient multimodal inference (image, video, voice)

→ On-device AI + edge personalization

→ Real-time cross-device continuity (Android ↔ TV ↔ Web)

→ Multi-category shopping catalog integrated with GenAI

→ Commerce + ads intelligence optimizing in milliseconds

Lead with Technical Depth

- Guide teams on architecture, code quality, and operational excellence

- Conduct design and code reviews with a high bar for clarity and maintainability

- Mentor engineers and elevate engineering culture

Operate Like an Owner

- Drive features from concept → design → production → on-call → iteration

- Collaborate across product, design, ads, AI/ML, and commerce — no silos

- Balance speed and quality in a high-velocity environment

Think Beyond the Code

- Translate complex engineering into simple narratives for stakeholders

- Anticipate system-wide consequences of design choices

- Shape technical roadmap with business context

WHAT WE EXPECT

Core Technical Expertise (7–10+ years)

- Distributed systems: partitioning, replication, consistency, failure modes

- Cloud platforms (GCP/AWS), Kubernetes, containerization, CI/CD

- Databases: SQL + NoSQL trade-offs, indexing, query optimization

- Strong in Java/Kotlin, Go, or Python

- High-performance, multi threaded, low-latency systems

Data & Infrastructure

- Large-scale pipelines: Kafka, Spark, Flink

- Cost-efficient cloud design & operations

- Observability mindset: metrics, tracing, alerting

- Comfortable with OSS, reading source, contributing when needed

Ways of Working

- Writes clear RFCs/design docs that ship

- Leads through ambiguity in high-stakes environments

- Adapts to shifting priorities without losing quality

- Uses GenAI tools to accelerate problem-solving

WHY JOIN US

- Real scale: AI workflows across GPU clouds + Android + TV

- Cutting-edge: GenAI, multimodal inference, on-device ML

- Full stack commerce: inspiration → visualization → purchase

- Impact: products reaching millions daily

- Ownership: architect and ship, not just maintain

What will you be doing?  

• Responsible for design, architecture, and delivery of a feature or component/product with the highest quality.  
• Driving innovations in the platform constantly & remaining ahead of the curve  
• Collaborates effectively with cross functional teams to deliver end-to-end products & features  
• Collaborates with non-tech stakeholders without technology barrier to align strategies with solutions
• Demonstrates ability to multi-task and re-prioritize responsibilities based on changing requirements  
• Provide functional, design, and code reviews in related areas of expertise with-in team and cross-team  
• Mentors/coaches engineers to facilitate their development and provide technical leadership to them
• Rises above detail to see broader issues and implications for whole product/team
• Collaborate with managers and enable them to size and estimate solutions better

What do we expect from you?  

• BS/MS in Computer Science or equivalent from a premier institute 
• 7-10 years of strong design/development experience in building massively large scale distributed internet systems and products 
• Extensive experience in developing and maintaining large scale systems on Cloud 
• Knowledge of architectural styles and design patterns. Deep understanding of Microservices architecture, Cloud computing, Big Data Technology and NoSQL database. 
• Excellent Java programming skills and expertise in multi-threading and performance oriented programming. 
• Excellent data structures & algorithms skills 
• Experience and knowledge of open source software, frameworks and broader cutting edge technologies around server side development in Java and Big Data 
• Superior organization, communication, interpersonal and leadership skills 
• Excellent grasp of the system, with the ability to effectively communicate with stakeholders and provide clear, insightful answers regarding the current system
• Must be a proven performer and team player that enjoy challenging assignments in a high-energy, fast growing and high velocity workplace 
• Must be a self-starter who can work well with minimal guidance and in fluid environment 
• Must be excited by challenges surrounding the development of massively scalable & distributed system 
• Agility and ability to adapt quickly to changing requirements and scope and priorities 
• Adapt to Gen-AI usage in problem solving and coding 

Nice to have skills  

• Experience of building products that are powered by data & insights 
• Experience in data sciences & machine learning 
• Experience of working on massively large scale data
• Experience in Google Cloud Platform
• Experience in navigating and contributing to Open Source Software (OSS)
• Experience in data security

Glance - An InMobi Group Company    

Founded in 2019, Glance is a consumer technology company that operates disruptive digital platforms including Glance, Roposo, and Nostra. Glance’s ’smart lock screen’ inspires consumers to make the most of every moment by surfacing relevant experiences without the need for searching and downloading apps. Glance Lock Screen is currently available on over 450 million smartphones worldwide. Roposo is a LIVE platform that is revolutionizing live experiences, through a unique, immersive, creator-led approach. Nostra is the largest gaming platform in India and Southeast Asia, offering gamers engaging ways to discover, play, watch, learn and compete.   
 
Headquartered in Singapore, Glance is an unconsolidated subsidiary of InMobi Group and is funded by Jio Platforms, Google, and Mithril Capital. For more information visit glance.com, nostra.gg, and roposo.com

What should you know about joining Glance?  

At Glance, we walk the talk – free yourself, dream big, and chase your passion! On joining, you’ll have opportunities to make an immediate impact on mission-critical projects, as you work with highly capable and ambitious peer groups.   

Be rewarded for your autonomy even as you collaborate. Ideate, innovate, and inspire by leveraging bleeding-edge tech to disrupt consumer experiences.   

While you work, we’ll take care of nourishing your body, mind, and soul. This includes daily meals, gym, trainings, tech tools, and regular unwind sessions. Also, feel free to bring your kids – even the furry ones – to the office!

What You’ll Do

As a Data Scientist – Recommendation Systems, you will own and drive high-impact ML systems powering personalization across Glance products.

• Design, build, and deploy large-scale recommendation and personalization models using diverse, high-volume data sources.
• Lead rapid experimentation—from hypothesis formulation to offline evaluation and online A/B testing—balancing speed, rigor, and business impact.
• Develop and productionize end-to-end ML pipelines, including data preparation, feature engineering, model training, evaluation, and monitoring.
• Partner closely with Product, Engineering, Design, UX, and Business teams to translate product goals into scalable ML solutions.
• Monitor model health and performance, applying statistical techniques to ensure robustness and long-term effectiveness.
• Explore and prototype new ML techniques to improve relevance, engagement, and monetization.
• Act as a technical interface for stakeholders, clearly articulating trade-offs, results, and next steps.
• Contribute to Glance’s thought leadership through blogs, case studies, and industry conference talks.

What We’re Looking For

Core Expectations

• Deep expertise in Machine Learning, Data Science, and Recommendation Systems at scale.
• Strong applied understanding of experimentation, metrics, and causal reasoning in real-world systems.
• Ability to take models from idea → prototype → production → business impact.

Experience & Skills

• 10+ years of industry experience in ML/Data Science building large-scale recommendation or personalization systems.
• Hands-on experience applying techniques from ML, Deep Learning, NLP, Reinforcement Learning, Time Series, and Statistics.
• Strong programming skills in Python with production-quality code practices.
• Experience with big data ecosystems, especially Apache Spark.
• Familiarity with cloud platforms such as AWS, GCP (Vertex AI), or Azure.
• Experience operating in identity-constrained / privacy-aware environments (e.g., iOS/Android, identity-less systems) is a plus.
• Excellent communication skills—able to explain complex technical ideas clearly to non-technical stakeholders.
• High curiosity, strong problem-solving ability, and a bias toward learning and experimentation.

Qualifications

• Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Electrical Engineering, Statistics, Mathematics, Operations Research, Economics, Analytics, or Data Science.
• PhD is a plus, but not mandatory.
• We value diverse academic backgrounds—great data scientists come from many disciplines.