AI/ML Architect

Sutherland Global; Chennai District; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

Sutherland Global is seeking an experienced AI/ML Architect to design end-to-end ML systems, deploy production models, and lead a team of ML engineers. The role demands strong coding in Python, hands-on ML framework experience, and the ability to translate client problems into scalable ML solutions.

You will mentor a team, conduct code reviews, and engage in pre-sales engagements, operating within an agile environment. Join a leader in digital transformation and enterprise AI delivery.

Qualifications

• 10+ years overall experience in ML/AI/data science.
• 6+ years in ML with 3+ years in architect/lead role.
• Strong Python and production ML experience.
• Proven in moving models from prototype to production.
• Experience reviewing ML pipelines and deployments.
• Hands-on with supervised learning, time-series, anomaly detection.
• Knowledge of MLOps and model lifecycle management.
• Cloud ML services on Azure/AWS/GCP.
• Proficient in SQL and large-scale data processing.
• Familiarity with version control systems.

Responsibilities

• Design end-to-end ML architectures across data ingestion, feature engineering, training, deployment, and monitoring.
• Review ML pipelines, models, and deployment scripts to ensure quality.
• Build and deploy production ML models using LightGBM, XGBoost, scikit-learn, PyTorch, TensorFlow.
• Implement MLOps including versioning, monitoring, retraining, and drift detection.
• Optimize model performance and diagnose data quality issues in production.
• Translate client problems into technically sound ML solutions.
• Lead and mentor ML engineers and data scientists with coding standards.
• Serve as technical authority in client discussions and pre-sales.
• Scope and estimate new ML opportunities and support proposals/RFPs.
• Work within an agile scrum framework and coordinate with multiple teams.

Skills

Python

Production ML

Code reviews

ML architectures

MLOps

Cloud platforms

SQL

Git

Problem solving

Data processing

Education

MS/PhD

Tools

LightGBM

XGBoost

Scikit-learn

PyTorch

TensorFlow

Databricks

Spark

REST API

Git

SVN

Job description

Company Description:

About Sutherland

Artificial Intelligence. Automation.Cloud engineering. Advanced analytics.For business leaders, these are key factors of success. For us, they’re our core expertise.

We work with iconic brands worldwide. We bring them a unique value proposition through market-leading technology and business process excellence.

We’ve created over 200 unique inventions under several patents across AI and other critical technologies. Leveraging our advanced products and platforms, we drive digital transformation, optimize critical business operations, reinvent experiences, and pioneer new solutions, all provided through a seamless “as a service” model.

For each company, we provide new keys for their businesses, the people they work with, and the customers they serve. We tailor proven and rapid formulas, to fit their unique DNA.We bring together human expertise and artificial intelligence to develop digital chemistry. This unlocks new possibilities, transformative outcomes and enduring relationships.
Sutherland

Unlocking digital performance. Delivering measurable results.

Job Description:

We are seeking an experienced AI/ML Architect with strong expertise in machine learning system design, production model deployment, and hands‑on coding ability. The ideal candidate will be highly skilled in architecting end‑to‑end ML solutions, conducting code reviews across ML pipelines, and delivering scalable predictive analytics systems for enterprise clients. This is a hands‑on architecture role requiring both technical depth and delivery leadership.

Key Responsibilities:

• Design, develop, and maintain end‑to‑end ML architectures covering data ingestion, feature engineering, model training, deployment, and monitoring.
• Perform code reviews across ML pipelines, model implementations, and deployment scripts to maintain engineering quality standards.
• Build and deploy production machine learning models using frameworks such as LightGBM, XGBoost, scikit‑learn, PyTorch, and TensorFlow.
• Implement MLOps practices including model versioning, monitoring, retraining pipelines, and drift detection.
• Optimize model performance, diagnose data quality issues, and resolve production model degradation.
• Translate ambiguous client problem statements into technically sound, deliverable ML solutions.
• Lead and mentor a team of ML engineers and data scientists, establishing coding and validation standards.
• Act as technical authority in client discussions, solution workshops, and pre‑sales engagements.
• Scope and estimate new ML opportunities and support proposals and RFP responses.
• Working under a dynamic agile based environment.
• Strictly adhere to scrum framework and guidelines.
• Coordinate with multiple development teams.

Qualifications:

Required Skills & Experience:

• Overall experience: 10+ Years
• 6+ years of professional experience in machine learning, data science, or applied AI, with 3+ years in an architect or technical lead capacity.
• Strong hands‑on coding proficiency in Python with production ML framework experience.
• Demonstrated experience taking models from prototype to production, not limited to POC or research work.
• Proven ability to conduct code reviews across ML pipelines, data engineering, and model deployment.
• Hands‑on experience with classical ML techniques including supervised learning, anomaly detection, time‑series analysis, and imbalanced classification.
• Working knowledge of MLOps tooling and production model lifecycle management.
• Cloud platform experience (Azure, AWS, or GCP) including ML services and deployment infrastructure.
• Proficiency with SQL and large‑scale data processing.
• Familiarity with version control systems (Git, SVN, etc.).
• Strong problem‑solving skills and ability to work independently.

Preferred Skills:

• Experience with predictive maintenance, hardware failure prediction, or IoT/telemetry data.
• Exposure to log analytics, observability data, or large‑scale unstructured data processing.
• Experience with Databricks, Spark, or similar distributed data platforms.
• Knowledge of REST API integration for model serving and inference endpoints.
• Client‑facing consulting or services delivery background.
• Advanced degree (MS or PhD) in Computer Science, Statistics, Applied Mathematics, or related field.
• Experience in agile development environments.