Headline

Senior MLOps Engineer | AI Platform & LLMOps | Scaling Production ML Systems

About

I design and scale ML platforms that enable teams to build, deploy, and operate AI systems at enterprise scale. I have worked across SAP, 7-Eleven, and Mu Sigma, taking ML and LLM systems from prototype to production with a focus on platformization, reliability, and measurable business outcomes. My core focus areas: - MLOps and LLMOps platform design (CI/CD, observability, governance) - Scalable microservice-based ML systems on Kubernetes - Real-time data infrastructure (Kafka, Spark, Databricks) - Enterprise deployment workflows (MLflow, ArgoCD, GitHub Actions) Selected impact: - Scaled AIOps platform to 12M+ API calls/month across Fortune 500 clients - Reduced ML release cycles by 45% via end-to-end CI/CD automation - Improved deployment reliability by 60% using containerized, auto-scaling systems - Delivered $1.2M+ annual cost savings through data platform optimization I focus on establishing engineering standards, improving system reliability, and enabling cross-team adoption of ML systems at scale. Currently focused on building AI platforms that improve reliability, standardization, and velocity across ML teams.

Location

Greater Bengaluru Area

AI stack

claude code

claude

codex

github copilot

huggingface

Wispr Flow

Work experience

Senior MLOps Engineer | AIOps Platform Lead at SAP, Dec 2024 - Present · 1 yr 9 mos, Bengaluru, • Led the productionization and scaling of an enterprise AIOps platform serving 10+ Fortune 500 clients, processing 5M+ API calls/month • Architected microservice-based ML infrastructure on Kubernetes, improving deployment reliability by 60% through auto-scaling and fault-tolerant design • Built end-to-end MLOps and LLMOps workflows (GitHub Actions, ArgoCD, MLflow), reducing release cycles by 45% • Built NLP-driven anonymization pipelines, improving processing throughput by 40% while ensuring compliance with enterprise data privacy standards • Established DevSecOps practices (RBAC, SAST, dependency scanning), reducing security vulnerabilities by 30% • Drove cross-functional alignment across data engineering, platform, and product teams to standardize ML deployment and monitoring workflows • Led execution across multiple teams, improving delivery velocity by 25% Tech Stack: Python, Kubernetes, Docker, MLflow, ArgoCD, GitHub Actions, Databricks, REST APIs, Microservices

Senior AI & Machine Learning Engineer at 7-Eleven, Jul 2022 - Oct 2024 · 2 yrs 4 mos, Bengaluru, • Built an enterprise analytics interface using LLMs and LangChain, enabling self-serve data access and reducing dependency on BI teams • Designed real-time data pipelines (Kafka, Spark, Databricks) processing 600B+ records, improving query latency by 70% • Architected scalable ML deployment workflows using Docker and Kubernetes, enabling reproducible and reliable model releases • Developed LLM-driven systems for knowledge retrieval and analytics automation across enterprise datasets • Led migration of 300B+ rows across 250+ tables to Delta Lake and Power BI semantic layer, enabling unified real-time analytics • Mentored a team of 3 engineers on data pipeline design and production ML practices, improving delivery quality and system reliability • Presented system architecture and business impact to CXO-level stakeholders, aligning technical execution with organizational goals Tech Stack: Python, Kubernetes, Docker, Kafka, PySpark, Databricks, Apache Airflow (Astronomer), MLflow, Azure, Power BI, Delta Lake, LangChain

Lead Data Scientist at Mu Sigma Inc., Sep 2018 - Aug 2022 · 4 yrs, Bengaluru, Promoted from Data Scientist → Senior Data Scientist → Lead Data Scientist within 4 years • Led data science and data engineering initiatives for Fortune 300 clients, delivering predictive systems for demand forecasting, anomaly detection, and workforce analytics • Built ML pipelines using Airflow and cloud platforms (Azure, GCP), enabling scalable and repeatable model deployment workflows • Built batch and near real-time data processing systems using PySpark, improving data-to-decision cycle time by 40% • Partnered with VP and Director-level stakeholders to define AI strategy, system requirements, and business KPIs • Drove cross-functional collaboration across data, engineering, and business teams, improving delivery efficiency by 30% • Led and mentored teams across multiple projects, standardizing development practices and improving overall execution quality Tech Stack: Python, PySpark, Airflow, Azure, GCP, SQL, Power BI

Technical Writer - AI, MLOps & LLM Systems at Medium, Jan 2018 - Sep 2024 · 6 yrs 9 mos, Remote, • Published articles on AI infrastructure, MLOps, and LLM systems across Towards Data Science and DataDriven Investor, reaching 230K+ global readers • Wrote technical deep dives on ML system design, LangChain, and production ML workflows • Recognized as a Top Writer on Medium for translating complex AI concepts into practical, implementation-focused insights • Published content focused on helping engineers understand and apply production-grade ML systems

Instructor & Technical Educator - AI/ML at Anish Mahapatra, 2017 - Jul 2023 · 6 yrs 7 mos, India, • Conducted live sessions on Data Science, ML, and AI for 50K+ learners, maintaining an average CSAT of 4.9/5 • Designed and delivered technical learning content on applied AI and ML systems, including structured courses, tutorials, and workshops • Mentored aspiring data professionals on project development and real-world ML applications • Invited speaker for webinars and technical sessions, translating complex concepts into practical insights for industry use

Education

Master's in Data Science, With Distinction (Top 1%), Data Science, Machine Learning and Artificial Intelligence (ML & AI), Liverpool John Moores University

B.Tech, Computer Science, Manipal institute of technology

Public links

github: https://github.com/anishmahapatra

medium: https://medium.com/@anishmahapatra