About the job

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!

Basic Qualifications

• 7+ years of experience developing and working with large scale ML Platforms.
• Experience managing large-scale ML infrastructure on multi-node multi-GPU clusters.
• Familiarity with public cloud platforms such as GCP, AWS, Azure, etc.
• Expertise in distributed computing frameworks such as Horovod, Ray, or SLURM.
• Proficiency in Docker, Kubernetes (K8s) and Kubeflow for orchestrating ML workloads.
• Strong software development skills in Python, with a focus on maintainability and performance.
• Strong proficiency in PyTorch for model development and deployment.
• Hands-on experience with multi-GPU and multi-node training.
• Ability to build and manage control planes and tools for efficient, secure, and scalable ML services.
• Experience with MLOps practices for managing production machine learning lifecycles.
• Experience optimizing ML models and infrastructure for performance, scalability, and cost-efficiency.
• Understanding of ML security best practices and safeguarding production systems.

Preferred Qualifications

• Advanced degree (Master’s or PhD) in Computer Science, Machine Learning, or related field.
• Experience with TensorFlow, PyTorch, and other deep learning frameworks.
• Familiarity with public cloud platforms such as GCP, AWS, Azure, etc.
• Experience with AutoML platforms and optimizing model training speed on GPU/TPU clusters.
• Strong background in causal inference, A/B testing, and experimentation.
• Experience working with vector similarity search, ranking systems, or recommendation systems.
• Track record of mentorship, collaboration, and driving technical roadmaps in ML teams.