Senior Machine Learning Engineer

GRhombus is hiring on behalf of a leading technology organization for a Senior Machine Learning Software Engineer.

The role is ideal for an experienced ML/Software Engineer who can build scalable machine learning infrastructure, MLOps platforms, automation frameworks, and production-grade systems. You will work across the machine learning lifecycle, bridging the gap between experimentation and reliable production deployment.

The position also involves technical leadership, architecture, engineering best practices, and mentoring junior engineers.

Key Responsibilities

ML Infrastructure & Platform Engineering

• Design, build, and maintain reusable components supporting ML model training, evaluation, deployment, and monitoring.
• Optimize model-serving frameworks, feature stores, data pipelines, and CI/CD systems for ML workflows.
• Build reliable, scalable, observable, and high-performance ML systems.

Technical Leadership

• Lead engineering initiatives involving ML platform stability, experimentation infrastructure, and real-time inference systems.
• Review code and contribute to architectural and technical decisions.
• Drive MLOps pipelines, automation, and model governance workflows.
• Establish and promote software engineering best practices within ML engineering teams.

Collaboration

• Work closely with ML researchers to transition experimental models into production-ready systems.
• Collaborate with data engineering teams on data pipelines, validations, and model input/output schemas.
• Partner with product engineering teams on ML-related APIs, system integrations, optimization, and inference requirements.

Mentorship & Knowledge Sharing

• Mentor junior ML Software Engineers and support their technical growth.
• Contribute to architecture reviews, technical documentation, and engineering learning initiatives.
• Promote high standards for code quality, reproducibility, scalability, and maintainability.

Required Skills & Experience

• 5–8 years of experience in ML engineering, backend engineering, or infrastructure roles supporting machine learning.
• Strong proficiency in Python.
• Proficiency in one or more systems-level programming languages such as Go, Java, or C++.
• Hands-on experience building and maintaining ML infrastructure.
• Experience with ML model registries, training orchestration, distributed data pipelines, or similar ML platforms.
• Experience with containerization and deployment technologies such as Docker and Kubernetes.
• Exposure to cloud ML platforms such as AWS SageMaker, Google Vertex AI, or equivalent.
• Experience with modern MLOps frameworks such as MLflow, Metaflow, TFX, Kubeflow, or similar technologies.
• Demonstrated experience mentoring junior engineers.

What We're Looking For

We are looking for an engineer who combines strong software engineering fundamentals with practical machine learning infrastructure experience and can contribute to building scalable, production-ready ML systems.

Location

Bengaluru | Chennai | Pune

How to Apply

Interested candidates can apply through LinkedIn or share their updated resume with [Confidential Information]