Machine Learning Engineer_5+yrs

Zorba AI; Chennai District; On-site; INR 1,500,000 - 2,500,000; Full time

Benefits offered by this job

Competitive compensation

Learning budget for advanced ML tooling

Opportunities for technical leadership

Job summary

A technology consulting firm is seeking a Senior Machine Learning Engineer to design and implement end-to-end ML solutions. This on-site role in Chennai involves productionizing models with MLOps best practices and requires expertise in Python, PyTorch, TensorFlow, and Kubernetes. Candidates will engage directly with clients, leading high-visibility projects and driving technical best practices. Competitive compensation, mentorship opportunities, and a learning budget are part of the benefits.

Qualifications

• Strong experience in designing and building ML systems.
• Knowledgeable in modern MLOps practices, deployment pipelines, and containerization.
• Ability to collaborate effectively with cross-functional teams.

Responsibilities

• Design and implement end-to-end ML solutions from data ingestion to deployment.
• Productionize models with MLOps best practices.
• Build scalable API services that meet latency and throughput requirements.
• Translate business requirements into ML deliverables with the team.
• Implement model monitoring and observability practices.
• Ensure code quality through mentorship and documentation.

Skills

Python

PyTorch

TensorFlow

Scikit-learn

Docker

Kubernetes

Tools

AWS SageMaker

MLflow

Apache Spark

Job description

A technology consulting firm operating in the IT Services & Data Science consulting sector, delivering enterprise-grade AI, ML, and analytics solutions to clients across finance, retail, and enterprise verticals. We build production ML systems that drive business outcomes, with a strong focus on model reliability, scalability, and MLOps best practices.

Senior Machine Learning Engineer (on-site, India)

Responsible for designing, building, and productionizing ML systems for high-impact customer engagements.

Role & Responsibilities

• Design and implement end-to-end ML solutions: data ingestion, feature engineering, model development, validation, and deployment to production.
• Productionize models with robust MLOps practices: containerization, CI/CD pipelines, model versioning, automated testing, and deployment orchestration.
• Build scalable inference services and APIs using container orchestration and scalable compute to meet latency and throughput SLAs.
• Collaborate with data engineers, product managers, and stakeholders to translate business requirements into measurable ML deliverables and deployment roadmaps.
• Implement monitoring, alerting, and model observability (performance, drift detection, and explainability) to ensure continuous model health in production.
• Drive code quality through reviews, mentoring junior engineers, and documenting reproducible experiments and engineering playbooks.

Skills & Qualifications

Must-Have

• Python
• PyTorch
• TensorFlow
• Scikit-learn
• Docker
• Kubernetes

Preferred

• AWS SageMaker
• MLflow
• Apache Spark

Benefits & Culture Highlights

• On-site role with direct client engagement and high-visibility projects across industries.
• Opportunities for technical leadership, mentorship, and contribution to engineering best practices and IP.
• Competitive compensation, learning budget for advanced ML tooling, and fast career progression for high performers.

Location: On-site (India). Candidates should be prepared for client-facing work, hands-on implementation, and delivering production-ready ML assets end-to-end.

Skills: machine learning,tensorflow,python,docker,scikit-learn,pytorch,kubernetes