Machine Learning Systems Engineer, Citi

Citi

Location:
India, Pune

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

ML Solutions team is seeking a skilled and innovative ML Systems Engineer with ML Ops experience to join our team. In this role, you will be responsible for building and maintaining scalable backend systems, deploying data science (DS) models, and designing robust pipelines that enable seamless integration of DS solutions into our applications. You will work closely with data scientists and front end engineers to help bridge the gap between data science and production-ready systems.

Job Responsibility:

Hands on development of ML Systems backend infrastructure, messaging and integration with interfacing systems
Design, build, and maintain APIs, Microservices, and systems to serve data science models
Ensure ML Infrastructure systems are scalable, reliable, and secure
Work with SQLAlchemy to define, maintain, and query the database schema for an application
Work with raw SQL to run advanced queries for things like alerting and reporting
Develop and maintain CI/CD pipelines for data science models and services
Automate and track data science workflows with tools like MLflow
Manage and optimize Kubernetes cluster via Openshift
Implement and manage various infrastructure components such as PostgreSQL, Kafka, S3
Work with data scientists to understand model requirements and ensure successful deployment into production systems
Collaborate with DevOps and infrastructure teams to improve scalability and reliability
Optimize backend services and data science model inference for latency and throughput
Troubleshoot issues in production environments, ensuring high availability of services
Drive the adoption of modern engineering ways of working, including Agile, DevOps, and CI/CD
Advocate for automated testing, infrastructure as code, and continuous monitoring to enhance software reliability
Apply Behavior-Driven Development (BDD), Test-Driven Development (TDD), and unit testing to ensure code quality and functionality
Conduct thorough code reviews, ensuring adherence to best practices in readability, performance, and security
Implement and enforce secure coding practices, performing vulnerability assessments and ensuring compliance with security standards
Collaborate effectively in agile environments, embracing DevOps principles and fostering a culture of continuous delivery and improvement

Requirements:

Proficiency in Python
Hands on experience working with a Python web framework such as FastAPI, Flask, Django, etc
Peripheral knowledge in Machine Learning and Data Science
Working knowledge in MLOps principals such as experiment tracking, model serving, model orchestration, etc
Hands on experience with designing DB driven applications and using an ORM such as SQLAlchemy
Hands on experience with deploying and maintaining production applications
Hands on experience with managing and debugging the necessary infrastructure to support a full stack application
Hands on experience with Kubernetes
Hands on experience working with stream processing tools like Kafka or Apache Spark
Bachelor's degree or equivalent experience in Computer Science or a related field

Nice to have:

Hands on experience working with a Python orchestrator (Dagster, Airflow, Prefect, etc)
Hands on experience working with various MLOps tools such as MLFlow, Kedro, etc
Hands on experience working with LLMs and related technologies such as Vector DBs, Agents, etc
Knowledge of running workloads in AWS or GCP

Additional Information:

Job Posted:
September 12, 2025

Employment Type:

Fulltime

Work Type:

On-site work

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Machine Learning Systems Engineer