Role description
Work Timings 1.30PM - 10.30 PM
Location- Bellandur Bangalore
WFH- Monday
WFO- Tuesday- Friday
Role Summary
Experience Range 8- 10 years
We are seeking a Software Engineer with strong Python and MLOps foundations to build enhance and stabilize a productiongrade AI ML-ops platform supporting model training validation deployment and orchestration at enterprise scale
This role goes beyond scripting or notebookdriven ML You will work in a classbased APIdriven CICDenforced MLOps ecosystem contributing to reusable libraries ML workflows secure endpoints JSONschemadriven interfaces and automated pipelines aligned with Chevrons evolving GitHub Actions strategy
Key Responsibilities
Core Engineering MLOps
Design build and maintain productiongrade Python services using sound objectoriented principles SOLID separation of concerns reusability
Contribute to and extend the enterprise MLOps pipeline supporting
Model training validation and registration
Azure MLbased execution
Parameterized workflow orchestration
CICDdriven deployments
Implement and maintain ML inference endpoints with focus on
Highperformance IO using async programming and concurrency
Clean requestresponse contracts driven by JSON schemas
Robust validation and error handling
Develop welldefined APIs REST with
OpenAPI Swagger documentation
Versionaware schemas and backward compatibility considerations
Support platform evolution from Azure Pipelines to GitHub Actions contributing to
Pipeline rearchitecture
Build test and release automation
Secure artifact promotion across environments
Data ML Storage
Work with Pandas and Polars for feature handling transformations and data preparation
Support ML workflows leveraging ScikitLearn models and pipelines
Integrate with Azure Blob Storage and Azure Data Lake for model artifacts datasets and metadata
Nice to have Contribute to solutions involving Azure Cosmos DB for metadata or workflow state tracking
Quality Testing Maintainability
Write clean maintainable and testable codeoptimizing for longterm platform health over shortterm delivery speed
Expand and strengthen the automated test suite including
PyTestbased unit and integration tests
Validation of pipelines schemas and services
Advocate for and gradually adopt TestDriven Development TDD practices across the codebase
Actively reduce technical debt in a legacyheavy environment by
Refactoring duplicated or brittle code
Introducing shared libraries and abstractions
Improving documentation and developer ergonomics
Required Technical Skills
Advanced Python
Classbased design modular architecture reusable components
Not scriptonly or notebookcentric development
API Development
RESTful services endpoint performance tuning
OpenAPI Swagger documentation
Async Programming
Asyncawait concurrency threading for IOheavy workloads
CICD
Azure Pipelines andor GitHub Actions
Experience evolving pipelines not just consuming them
Data ML
Pandas Polars
ScikitLearn
Testing
PyTest
Strong appreciation for automated testing as a quality gate
SchemaDriven Development
JSON schemas for configuration workflow parameters and APIs
Experience updating and managing schema evolution
NicetoHave Skills
Azure ML SDK training pipelines model registration
Pydantic for requestresponse validation
Azure Cosmos DB
Schema versioning strategies
Experience with large shared enterprise codebases
Desired Qualities Mindset
Takes Initiative
Understands how individual stories connect to platformlevel objectives
Proactively improves systems instead of waiting for direction
Strong Debugger
Comfortable tracing failures across pipelines services storage and infrastructure
Attempts rootcause analysis before escalating issues
Values Code Quality
Will not compromise maintainability for speed
Actively resists adding to technical debt
Engineering Craftsmanship
Cares about design clarity and longterm scalability
Sees MLOps as software engineering not just ML enablement
Advocates for Better Practices
Encourages testability consistency and clean abstractionseven in legacy environments
Skills
Mandatory Skills : MLOPS - Python
About LTM
LTM is an AI-centric global technology services company and the Business Creativity partner to the world’s largest and most disruptive enterprises. We bring human insights and intelligent systems together to help clients create greater value at the intersection of technology and domain expertise. Our capabilities span integrated operations, transformation, and business AI — enabling new ways of working, new productivity paradigms, and new roads to value. Together with over 87,000 employees across 40 countries and our global network of partners, LTM — a Larsen & Toubro company — owns business outcomes for our clients, helping them not just outperform the market, but to Outcreate it. Please also note that neither LTM nor any of its authorized recruitment agencies/partners charge any candidate registration fee or any other fees from talent (candidates) towards appearing for an interview or securing employment/internship. Candidates shall be solely responsible for verifying the credentials of any agency/consultant that claims to be working with LTM for recruitment. Please note that anyone who relies on the representations made by fraudulent employment agencies does so at their own risk, and LTM disclaims any liability in case of loss or damage suffered as a consequence of the same. Recruitment Fraud Alert - https://www.ltimindtree.com/recruitment-fraud-alert/
