Senior MLOps Engineer

Posted 8 Hours Ago
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Pune, Mahārāshtra, IND
In-Office
Senior level
Business Intelligence
The Role
Design, build, and maintain scalable MLOps platforms and CI/CD pipelines. Containerize and orchestrate workloads, implement model versioning and monitoring, deploy models as APIs, optimize serving performance, and enforce security and governance while collaborating with data and platform teams to productionize ML solutions.
Summary Generated by Built In

About the Job

About Aligned Automation

At Aligned Automation, we live by our "Better Together" philosophy to build a better world. As a strategic service provider to Fortune 500 companies, we help digitize enterprise operations and drive impactful business strategies. Our purpose goes beyond projects—we strive to deliver meaningful, sustainable change that shapes a more optimistic and equitable future.

Our culture is deeply rooted in our 4Cs—Care, Courage, Curiosity, and Collaboration—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 langfuse.
  • 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.



Skills Required

  • 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 building and optimizing CI/CD pipelines (GitLab CI, Jenkins, or similar).
  • Experience with MLflow, Kubeflow, Airflow, or similar MLOps orchestration tools.
  • Experience with Spark/PySpark and distributed data processing.
  • Knowledge of REST/gRPC 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.
  • Experience with Large Language Models (LLMs), RAG, vector databases, or LangChain/langfuse.
  • 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.
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The Company
HQ: Irving, TX
344 Employees
Year Founded: 2018

What We Do

Technology, society, economy, policy – all moving at breakneck speed in our 21st century world. You’re feeling the pressure to quickly implement new business models, find new value, make split-second informed decisions and keep one step ahead of customers. How? The answer lies in the ability to make quick, accurate and sustainable business decisions. We believe digital offers a way of doing things better – but the journey to transformation doesn’t have to be painful. At Aligned Automation, we work hard to digitally enable your business strategy – connecting processes, technologies and people to unlock value and drive critical business outcomes.

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