Myntra
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Bengaluru · On-site · 5-8 Yrs · 1 day ago
Internet & Web Services · 1001 to 5000 Employees · Bengaluru, India
We’re Myntra, India’s leading fashion and lifestyle destination where tech meets trendsetting style. Launched in 2007 as a portal for personalized gifts, we pivoted into fashion in 2011 and have been redefining how India shops ever since. From launching our first in-house brand Roadster Life Co. to introducing industry-firsts like app-only retail in 2015, Try & Buy in 2016, AI-led fashion design in 2018, and India’s first digital mall in 2020, we’ve consistently stayed ahead of the curve. Whether it’s real-time style advice with FashionGPT, live shopping through M-Live, or ultra-fast delivery with M-Now, innovation is part of everything we do. Today, Myntra connects millions of customers with the best of fashion, from iconic global brands to emerging local labels, all powered by data, creativity, and a deep passion for self-expression. We’re not just building a marketplace. We’re fashioning the future.
What employees say
+ Good worklife balance and work culture Flexible timings Good work
− The ratings and annual compensation and promotions system can be revamped a lot
More reviews on the company profile.
Interview experience · Operations Manager
There were 4 rounds plus 1 HR round in the end. It was about my past experience with Amazon, situation based questions to gauge ownership, team building, conflict handling, task prioritization etc, understanding on excel
Average difficulty · India · 383 reports
More interview insightsJob description
Overview
Build the Platform Behind AI at Myntra
Responsibilities
- Build developer-facing platforms, SDKs, APIs and abstractions.
- Reduce the time required to move an ML experiment into production.
- Eliminate repetitive infrastructure work for Data Scientists and ML Engineers.
- Build standardized templates and paved roads for ML development.
- Improve debugging, discoverability and observability of ML workloads.
- Enable teams to focus on models and business problems rather than infrastructure.
- Own architecture and technical direction for major ML Platform initiatives.
- Lead complex system-design discussions and technical reviews.
- Convert ambiguous problems into scalable platform solutions.
- Drive engineering excellence across reliability, scalability, performance and maintainability.
- Mentor engineers and raise the technical bar of the team.
- Influence architecture across ML, Data, Platform, SRE and Infrastructure teams.
- Evaluate emerging technologies and make pragmatic build-vs-buy decisions.
- Take critical systems from concept through architecture, implementation and production adoption.
Qualifications
- 6+ years of strong hands-on software/platform engineering experience.
- Strong programming skills in Python.
- Deep hands-on experience with Kubernetes, containers and Linux.
- Strong understanding of cloud infrastructure including compute, storage and networking.
- Strong understanding of ML training and deployment workflows.
- Strong debugging and production troubleshooting skills.
- Strong fundamentals in system design, reliability and distributed computing.
- Ray or other distributed computing frameworks
- Distributed or multi-node ML training
- GPU and multi-GPU infrastructure
- Kubernetes-based ML platforms
- ML training platforms used by multiple teams
- Model serving and inference infrastructure
- GPU scheduling and utilization optimization
- Large-scale workflow orchestration
- ML platform developer experience
- Infrastructure cost and performance optimization
- Feature platforms or feature stores
- Databricks, SageMaker, Vertex AI or similar ML platforms
- Model monitoring, data drift and automated retraining
- NVIDIA Triton, Ray Serve, vLLM or SGLang
- LLM training/inference and LLMOps
- Vector databases and retrieval infrastructure
- Model governance and lineage
- OpenTelemetry, Grafana or similar observability ecosystems
- Strong Differentiators
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Job application FAQ
Last updated 22 September 2026
- How do I apply for Technical Lead-Machine learning at Myntra?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Myntra may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this Technical Lead-Machine learning role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is Technical Lead-Machine learning remote or on-site in Bengaluru, Karnataka?
- This listing is marked on_site with location Bengaluru, Karnataka. Confirm details on the job description before applying.
- What skills matter for this Technical Lead-Machine learning role at Myntra?
- This is a lead Technical Lead-Machine learning role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.