Partner with Data Scientists to deploy operationalize monitor and scale machine learning models in production environments
Design develop and deploy AIML and LLMpowered solutions including predictive models RAG applications AI copilots intelligent assistants and agentic workflows
Develop feature engineering batch scoring realtime inference and modelserving pipelines
Apply Machine Learning NLP Generative AI and Agentic AI techniques to automate business processes improve decisionmaking and enhance operational efficiency
Build prompt engineering vector search semantic retrieval and knowledgegrounding capabilities for enterprise AI applications
Support model experimentation validation retraining and continuous improvement initiatives
Design Build Data Engineering Solutions
Design develop and maintain scalable batch and streaming data pipelines supporting AI ML analytics and reporting use cases
Build and optimize data ingestion transformation and curation workflows using modern data platforms such as Databricks and Azure
Develop and maintain data products using lakehouse architectures Delta Lake medallion frameworks and enterprise data governance standards
Integrate structured and unstructured data sources to support AI and machine learning applications
Ensure data quality lineage observability reliability and performance of production data pipelines
Develop reusable datasets feature engineering pipelines and data assets that support model training and inference
Productionize AIML Models
Build scalable APIs microservices and AI services for model deployment and consumption
Implement MLOps and LLMOps practices including CICD automated testing model validation monitoring observability and performance optimization
Manage model lifecycle versioning deployment rollback strategies and continuous improvement in production environments
Implement model monitoring drift detection performance tracking ing and retraining processes
Optimize model inference latency scalability reliability and cost efficiency
Integrate with Enterprise Data Cloud Platforms
Integrate AIML models with enterprise applications business workflows and cloudnative architectures
Collaborate with data engineering architecture and platform teams to build and consume enterprise data products
Leverage Databricks Azure and cloudnative services to deliver scalable AIML solutions
Support AI Foundry and enterprise AI platform initiatives by developing reusable frameworks accelerators and shared services
Contribute to enterprise AIML platform capabilities including feature stores model registries prompt registries and deployment frameworks
Ensure Responsible AI Governance
Align AI and ML solutions with organizational governance compliance privacy security and Responsible AI standards
Implement monitoring explainability transparency auditability and risk controls across AIML solutions
Support model validation bias detection governance frameworks and regulatory compliance requirements
Ensure AI and ML solutions meet enterprise reliability security and operational support standards
Collaborate Drive Innovation
Partner with product owners architects data scientists data engineers and business stakeholders to deliver highimpact AIML solutions
Contribute to AI engineering MLOps data engineering and software development best practices
Develop reusable components frameworks and accelerators to improve delivery efficiency
Stay current with emerging trends in AI ML GenAI Agentic AI MLOps Data Engineering and cloudnative technologies
Required Qualifications
Bachelors or Masters degree in Computer Science Engineering Data Science Machine Learning or a related field
Minimum 5 years of experience building productiongrade AIML and data engineering solutions including at least 3 years of handson experience deploying and operating machine learning models in enterprise environments
Strong programming skills in Python and SQL with experience developing enterprisegrade applications
MLOps platforms and practices for model deployment monitoring and lifecycle management
Databricks Apache Spark Delta Lake and Lakehouse architectures
Generative AI and LLM platforms Azure OpenAI OpenAI Anthropic Claude Gemini
RAG architectures Vector Databases Embeddings and Prompt Engineering
AI orchestration frameworks such as LangChain LangGraph Semantic Kernel or CrewAI
Experience designing and building scalable data pipelines ETLELT processes and data products
Experience building REST APIs microservices and productiongrade AIML applications
Strong knowledge of feature engineering model serving inference pipelines and production ML workloads
Skills
Mandatory Skills : Cloud platforms & services, Databricks MLFlow, GenAI - LLMOps, MLOPS, Python
Valuable to Have Skills : Azure ML
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.ltm.com/careers/recruitment-fraud-alert