Machine Learning Engineer (Senior)

Overview

Job Type: Permanent - Full Time

Location: Hyderabad

Job Category: Engineering

Who is Quantium?

Quantium is a world leader in data science and artificial intelligence. Established in Australia in 2002, Quantium is a global team of more than 1,100 people across 14 locations with a unique blend of capabilities across product and consulting services to help businesses unlock value from data and analytics. Quantium partners with the world's largest corporations to forge a better, more insightful world.

The Senior ML Engineer is a technical individual contributor role within a cross-functional team responsible for designing, building, and deploying production-grade machine learning systems and data infrastructure. Based in Hyderabad, this role collaborates closely with ML Scientists and Data Engineers to own the end-to-end ML lifecycle—from data pipeline development to model deployment, monitoring, and optimization—ensuring ML models are scalable, reliable, and deliver business value in production environments.

How will you make an impact?

• Production ML Systems: Design, build, and maintain production ML systems that serve predictions at scale, including model training pipelines, feature stores, and serving infrastructure
• Data Pipeline Development: Develop and optimize data pipelines to support ML workflows, ensuring data quality, reliability, and efficient feature engineering
• MLOps Implementation: Implement MLOps best practices including model versioning, automated testing, monitoring, retraining strategies, and deployment automation
• Model Productionization: Collaborate with Data Scientists to productionize ML models, translating experimental code into robust, scalable production systems
• Workflow Orchestration: Build and maintain orchestration workflows using Airflow, Vertex AI, and Cloud Composer to automate ML pipelines and data processes
• API Development: Design and implement APIs for model serving and integration with downstream applications
• Continuous Improvement: Drive continuous improvement of ML infrastructure, tooling, and engineering practices across the team
  
  

• Technical ML Engineering Expertise: 4-6 years of experience in ML engineering, data engineering, or software engineering with significant ML component
• Production ML Track Record: Proven track record of deploying and maintaining ML models in production environments
• Cloud Platform Mastery: Strong experience with cloud platforms, particularly GCP (BigQuery, Vertex AI, Cloud Composer, Dataflow); AWS or Azure experience also valuable
• Data Pipeline Development: Hands-on experience building data pipelines and working with large-scale datasets (batch and streaming)
• Orchestration Tools: Demonstrated experience with orchestration tools (Airflow, Cloud Composer, Prefect, or similar)
• CI/CD Practices: Solid experience with CI/CD practices and tools (Jenkins, GitLab CI, GitHub Actions, Cloud Build)
• Project Management: Experience in supervising work as a senior team member, project manager, or team leader
• Stakeholder Management: Proven experience managing both internal and external stakeholders in deadline-driven environments
• People Leadership: Experience and interest in people management, mentoring, and development
• Educational Background: Tertiary qualifications in engineering, mathematics, actuarial studies, statistics, physics, or a related discipline
• Advanced Analytics Knowledge: Expertise in data preparation, feature engineering, foundational analytics concepts, model development, and training
  
  

Working at Quantium will allow you to challenge your imagination. You will get to solve complex problems using rigor, precision, and by asking great questions – but it also means you can think big, outside the box, and push your problem-solving skills to the max.

By Joining The Quantium Team, You'll Get To

• Forge your path: Shape your career journey with opportunities to move across different teams or offices
• Find your kind: Embrace diversity and connect with like-minded professionals
• Make an impact: Drive transformational outcomes for leading FMCG clients through data-driven solutions
  
  

• Flexible Work Arrangements: Achieve work-life balance with hybrid and flexible work arrangements
• Continuous Learning: Access to the Analytics Community, fostering development, thought leadership, and technical excellence through collaboration and best practice sharing
• Group and Health Insurance: Comprehensive coverage for you and your loved ones
• Supportive Environment: Modern, flexible, and supportive workplace dedicated to powering possibilities for our team members, clients, and partners