Lead Software Engineer - AI & Data

ROLE OVERVIEW

As a Lead Software Engineer – ML, you will guide the design, development, and delivery of Machine Learning solutions. You will work closely with data scientists, product partners, platform engineering teams, and business stakeholders to translate strategic goals into scalable ML architectures and production-grade systems. This role requires strong expertise in ML engineering, feature pipelines, cloud-native ML platforms, and best practices for deploying ML models at scale. You will provide technical leadership to ML engineers, set coding and design standards, and ensure solutions are built with performance, reliability, and explainability in mind.

ROLES & RESPONSIBILITIES

Delivery and Execution

· Lead end-to-end ML solution design, including feature pipelines, model architecture, evaluation frameworks, and production deployment strategies

· Oversee development of scalable ML pipelines for training, inference, monitoring, and automated retraining

· Drive best practices in model validation, bias analysis, experiments, hyperparameter tuning, and cross-validation

· Lead architecture decisions related to cloud ML infrastructure, data processing frameworks, and model-serving environments

· Ensure production readiness through robust logging, observability, model/version tracking, and monitoring of drift or degradation infrastructure, networking layers, and distributed environments

Support and Enablement

· Coach and mentor ML engineers and junior team members on ML engineering patterns, coding standards, and cloud-based ML deployment

· Collaborate with MLOps and platform engineering teams on environment provisioning, pipelines, deployment, and model governance

· Build documentation, runbooks, architecture diagrams, and reusable ML engineering templates

· Support troubleshooting of production ML issues, optimize model performance, and improve operational resilience

JOB REQUIREMENTS

Education and Certifications

· Bachelor’s or master’s degree in computer science, information systems, engineering, or a related field

· Certifications in ML/AI (TensorFlow, Databricks, AWS/GCP/Azure ML)are preferred

Required Experience

· 7–10 years of experience delivering ML systems or data-driven applications, including at least 2–3 years in a technical leadership or mentoring capacity within enterprise or GCC environments

· Hands-on experience designing, deploying, and operationalizing ML models (forecasting, recommendations, classification, NLP, etc.) using cloud-native ML platforms such as GCP Vertex AI or Azure ML

· Proven experience working with global engineering or cross-functional teams, participating in distributed development and production lifecycle workflows aligned with large-scale enterprise environments

Essential skills

· Advanced proficiency in Python, ML frameworks ( e.g.: scikit-learn, TensorFlow, PyTorch), and distributed processing (e.g.: Spark, Beam)

· Strong understanding of feature engineering, model evaluation, bias detection, explainable AI, and ML lifecycle management

· Hands-on experience with GCP Vertex AI (preferred), or similar cloud ML platforms

· Experience in CI/CD for ML (MLOps), including automated retraining, model monitoring, and deployment workflows

· Experience with data warehouses (Snowflake), analytics tools (Tableau), and structured/unstructured data processing

· Strong coding discipline—unit testing, documentation, version control, peer reviews

Desired skills

· Experience with GenAI, LLMs, prompt engineering, and RAG pipelines

· Knowledge of supply chain, retail, pricing, or customer analytics domains

· Familiarity with Kubernetes, Docker, serverless ML deployment, and event-driven data processing

· Exposure to advanced ML patterns (model orchestration, feature stores, model registry, online prediction services)

WHAT WE OFFER

· Be part of a globally recognized leader in the home improvement sector, committed to operational excellence and sustainability

· Opportunity to contribute to a rapidly expanding Global Technology Center (GTC) in Chennai, playing a vital role in global operations

· Exposure to diverse global technology environment and cross-functional team collaborations

· Competitive compensation package and comprehensive benefits

· Clear pathways for career advancement and continuous learning opportunities within a high-performance organization