Mlops Engineer

Year    IN, India

Job Description

Meet your recruiter



Shivani Agrawal


shivani.agrawal@intellia...
https://www.linkedin.com...

Vacancy details


AI/ML Engineering
Machine Learning Operations Engineer
Strong Middle
India
Hybrid

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Explore the future of FinTech! With superb engineering, we help the finance industry to change just in one click! Join the global Intellias team to develop top-of-the-line solutions for the world's leading FinTech companies.

What project we have for you


Nomo Fintech is a unique, Sharia-compliant digital banking and wealth proposition in the heart of London. We are not just another digital bank offering seamless banking experience with certainty, security and simplicity but more. Our mission is to help people sustain and grow their wealth for future generations. We do this by solving problems people have instead of just selling boring banking products. We achieve this in a socially responsible way, driven by innovation and backed by a leading financial institution who are in it for the long run.

What you will do


Deploy and maintain ML and GenAI models using AWS services, including SageMaker, Fargate, and Bedrock. Apply prompt engineering techniques to optimize GenAI model performance and reliability. Experience with Retrieval-Augmented Generation (RAG) applications is a plus. Assist in building and maintaining internal model-serving platforms to support development teams. Implement containerized services using Docker and deploy them to AWS infrastructure. Write Infrastructure-as-Code (IaC) using Terraform to automate cloud resource provisioning (nice to have). Participate in unit and end-to-end testing of ML pipelines, services, and monitoring workflows. Support model monitoring and health tracking using AWS CloudWatch and internal observability tools. Document internal systems and operational processes to ensure maintainability and reproducibility.

What you need for this


The ML Ops Engineer plays a critical role in the development, automation, and deployment of Machine Learning (ML) and Generative AI (GenAI) pipelines across AWS cloud environments. This hands-on role emphasizes building reproducible workflows, integrating observability tools, and enabling efficient, scalable model delivery. The position supports AI systems deployed in banking environments, where resilience and reliability are paramount.

Key Experience


Strong programming skills in Python, with experience in pandas, SQL, and ML frameworks (e.g., scikit-learn). Familiarity with AWS services such as Lambda, Glue, CloudWatch, and Bedrock. Experience with container workflows (Docker) and model lifecycle management. Foundational knowledge of observability practices and model deployment fundamentals. Interest or experience in supporting AI systems used by developers or analysts. Strong communication and documentation skills with a collaborative team mindset. Ability to assume ownership of assignments and consistently meet deadlines.

What it's like to work at Intellias


At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That's why we offer a range of benefits that support your well-being and charge your professional growth.

We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law.

We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

Skills


AI/ML


AWS


Docker


GenAI


Gitlab


Glue


Lambda


ML


MLOps


Python


SQL


Terraform

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Job Detail

  • Job Id
    JD3838882
  • Industry
    Not mentioned
  • Total Positions
    1
  • Job Type:
    Full Time
  • Salary:
    Not mentioned
  • Employment Status
    Permanent
  • Job Location
    IN, India
  • Education
    Not mentioned
  • Experience
    Year