Senior MLOps Engineer

Aligned Automation, LLC; Pune District; On-site; INR 1,800,000 - 3,400,000; Full time

Job summary

Aligned Automation Services Pvt Ltd in Pune is seeking an experienced MLOps Engineer to design, build, and maintain scalable ML platforms for training, deployment, and monitoring of models.

You will develop CI/CD pipelines, containerize apps with Docker, orchestrate workloads with Kubernetes, and collaborate with data scientists and software engineers to productionize ML solutions while upholding security and governance practices.

Qualifications

• Strong Python programming skills.
• Hands-on with Docker, Kubernetes, Helm for containerized deployments.
• Git with branching strategies and CI/CD workflows.
• Experience with MLflow, Kubeflow, Airflow for ML pipelines.
• Spark/PySpark experience for distributed data processing.
• REST APIs with FastAPI/Flask and microservices architecture.
• Linux and Bash scripting for automation.
• Model monitoring and governance capabilities.
• SQL/NoSQL databases experience.
• Solid software engineering practices and testing.

Responsibilities

• Design and maintain scalable MLOps platforms for training, deploying, monitoring, and managing ML models.
• Develop CI/CD pipelines for ML apps using GitLab CI, Jenkins, etc.
• Containerize applications using Docker and orchestrate workloads with Kubernetes.
• Build ML pipelines using Kubeflow, MLflow, Airflow, Argo Workflows, or similar tools.
• Implement model versioning, experiment tracking, model registry, and reproducible workflows.
• Deploy ML models as REST/gRPC APIs using FastAPI, Flask, or similar frameworks.
• Configure monitoring and logging using Prometheus, Grafana, Dynatrace, or Splunk.
• Optimize serving performance, scalability, and resource utilization.
• Collaborate with Data Scientists, Data Engineers, Platform Engineers, and Software Developers to productionize ML solutions.
• Ensure platform security, governance, and compliance (DevSecOps).
• Troubleshoot production issues and perform root cause analysis for ML workloads.

Skills

Python programming

Docker

Kubernetes

Git

CI/CD

MLflow

Kubeflow

Airflow

Spark

REST APIs

Linux

Bash

Model monitoring

SQL

NoSQL

Software engineering

Tools

Docker

Kubernetes

Helm

Git

MLflow

Kubeflow

Airflow

Spark

Job description

Aligned Automation Services Pvt Ltd | Full time

At Aligned Automation, we livebyour\"Better Together\"philosophy to build a betterworld. As a strategic service provider to Fortune 500 companies, we helpdigitize enterprise operations and drive impactful business strategies. Our purposegoes beyond projects—we strive to deliver meaningful, sustainable change thatshapes a more optimistic and equitable future.

Our culture is deeply rooted inour4Cs—Care,Courage,Curiosity,andCollaboration—ensuring that each employee is empowered to grow,innovate, and thrive in an inclusive workplace.

About the Role

Key Responsibilities

• Design, build, and maintain scalable MLOps platforms for training, deploying, monitoring, and managing machine learning models.
  


• Develop and optimize CI/CD pipelines for ML applications using GitLab CI, Jenkins etc.
  


• Containerize applications using Docker and orchestrate workloads using Kubernetes.
  


• Build and maintain ML pipelines using Kubeflow, MLflow, Airflow, Argo Workflows, or similar orchestration tools.
  


• Implement model versioning, experiment tracking, model registry, and reproducible ML workflows.
  


• Deploy ML models as REST/gRPC APIs using FastAPI, Flask, or similar frameworks.
  


• Configure monitoring, logging, and alerting using Prometheus, Grafana, Dynatrace, or Splunk.
  


• Optimize model serving performance, scalability, and resource utilization.
  


• Work closely with Data Scientists, Data Engineers, Platform Engineers, and Software Developers to productionize ML solutions.
  


• Ensure platform security, governance, and compliance following DevSecOps best practices.
  


• Troubleshoot production issues and perform root cause analysis for ML workloads.
  

Required Technical Skills

• Strong programming experience in Python.
  


• Hands-on experience with Docker, Kubernetes, Helm, and containerized deployments.
  


• Strong knowledge of Git, branching strategies, merge requests, and CI/CD.
  


• Experience with MLflow, Kubeflow, Airflow, or similar MLOps tools.
  


• Experience with Spark/PySpark and distributed data processing.
  


• Knowledge of REST APIs, FastAPI, Flask, and microservices architecture.
  


• Experience with Linux, Bash scripting, and automation.
  


• Familiarity with model monitoring, drift detection, feature stores, and model governance.
  


• Experience working with SQL and NoSQL databases.
  


• Strong understanding of software engineering principles, design patterns, testing, and code quality.

Preferred Skills

• Experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, and AI orchestration frameworks such as LangChain or lang-fuse.
  


• Experience with NVIDIA GPU workloads and model optimization.
  


• Knowledge of Kafka, RabbitMQ, or event-driven architectures.
  


• Exposure to feature stores such as Feast.
  


• Experience with OpenShift, Red Hat ecosystem, or enterprise Kubernetes platforms.
  


• Knowledge of security scanning tools such as Trivy, SonarQube, and vulnerability management.
  

Resource should be technically strong, should have good communication skills and experience in handling customer communications and leading a team working on multiple projects. He should be able to generate ideasdrive, customer communications and manage team to ensure quality delivery and great customer experience.