Staff Machine Learning Engineer - Recommendation Systems

Glance AI is an AI commerce platform shaping the next wave of e-commerce with inspiration-led shopping, less about searching for what you want and more about discovering who you could be. Operating in 140 countries, Glance AI transforms every screen into a stage for instant, personal, and joyful discovery, where inspiration becomes something you can explore, feel, and shop in the moment.

Its proprietary models, seamlessly integrated with Google’s most advanced AI platforms, Gemini and Imagen on Vertex AI, deliver hyper-realistic, deeply personal shopping experiences across categories such as fashion, beauty, travel, accessories, home décor, pets, and more. Designed to seamlessly integrate into everyday consumer technology, Glance AI reimagines the future of e-commerce with inspiration-led discovery and shopping.

With an open architecture built for effortless adoption across hardware and software ecosystems, Glance AI is creating a platform that can become a staple in everyday consumer technology. It partners with the world’s leading smartphone makers, connected TV manufacturers, telecom providers, and global brands — meeting people where they are: on mobile, smart TVs, and brand websites.

Through Glance AI’s rich first-party data and unparalleled consumer access, it harnesses InMobi’s global scale, insights, and targeting capabilities to create high-impact, performance-driven shopping journeys for brands worldwide. Part of the InMobi Group, a global technology and advertising leader reaching over 2 billion devices and serving more than 30,000 enterprise brands worldwide, Glance AI is backed by Google, Jio Platforms, and Mithril Capital.

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 Data Scientist who will design and develop recommendation systems on high volume, diverse "big data" sources using advanced mathematical, statistical, querying, and reporting methods. Will use machine learning techniques and statistical analysis to predict outcomes and behaviors.

• Develop and deploy machine learning models with a focus on quick, reliable experimentation to validate features and hypotheses. Our team values speed and quality in experimentation. 

• Assist in building and maintaining machine learning pipelines, aiding in tasks such as data preparation, model training, and evaluation. 

• Collaborate closely with Designers, UX Researchers, Product Managers, and Software Engineers to contribute to the integration of machine learning solutions into Glance's products. 

• Monitor the health and performance of machine learning models, using statistical methods to ensure their effectiveness. 

• Conduct preliminary research and development in machine learning techniques to enhance Glance's product capabilities. 

• Additionally, stakeholder management is needed. It will involve being the interface with internal stakeholders such as our Product, Engineering, Data, Infrastructure, and Business teams. 

• You will work in a multi-functional team environment. You will collaborate and benefit from the skills of a diverse group of individuals from teams such as engineering, product, business, campaign management and creative development.

• We are a company that innovates and demonstrates our thought leadership to the world. We encourage and support all team members to write blogs, commentary and case studies published on the Glance blog. We also support team members across our ML/AI team to speak at industry conferences and represent Glance’s work. 

The experience we need 

• Candidates are expected to have deep expertise and experience in AI/ML, Recommendation Systems and Data Science, particularly at scale. Familiarity with big data processing and cloud computing will be critical to succeed in this environment. 

• In addition to possessing a mathematical aptitude, they need to be competent with data science languages and tools which will enable them to design scalable solutions for our advertising products, implement proof-of-concept, and evaluate them offline and online. They will also need to work with other engineers to take these solutions to live production and drive real business value. 

• Most importantly, we look for a passion to investigate and learn about the world from data, to ask interesting and provocative questions, and be driven to put real models into production that drive real business value. 

• We are open to diverse academic backgrounds, providing an intent to think and problem-solve like a data scientist. Our team includes engineers, mathematicians, computer scientists, physicists, economists and social scientists – a rock-star data scientist can come from any academic field. 

Qualifications 

• Bachelors/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. PhD a plus. 

• 10+ years of ML industry experience working in Data Science teams, ideally in recommendation systems and personalization at scale. You would have applied algorithms and techniques such as NLP, Reinforcement Learning, Time Series, etc. from Machine Learning, Deep Learning, and Statistics or other domains in solving real world problems and understand the practical issues of using these algorithms especially on large datasets. 

• Comfortable with software programming and statistical platforms such as R, Python etc. 

• Comfortable with the big data ecosystem and Apache Spark. Familiarity with Microsoft Azure, AWS, or Google Cloud/Vertex AI will be a bonus. 

• Comfortable collaborating with cross-functional teams. 

• Familiarity with challenges of the identity-less world, particularly for iOS and Android 

• 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 and technology 

"Glance collects and processes personal data such as your name, contact details, resume and other information that may contain personal data for the purpose of processing your application. Glance utilizes Greenhouse, a third-party platform. Please review Greenhouse's Privacy Policy to understand how the data collected from you is processed and managed. By clicking on 'Submit Application', you acknowledge and agree to the above privacy terms. Should you have any privacy concerns, you may contact us through the details mentioned in your application confirmation email."