Machine Learning Engineer III

Overview

Build and deploy ML-based solutions for CommerceIQ's B2B SaaS retail ecommerce platform, working with Data Science, Engineering, Platform, Product and Operations teams.

What you'll do

• Contribute to development of multiple AI-driven end-to-end pipelines that allow deployment and scalability of machine learning models
• Build an end-to-end machine learning platform covering all lifecycle stages of a model, to ease model development and deployment
• Build tools and capabilities for data ingestion to feature engineering, data management and organisation
• Deploy cutting-edge algorithms like LLMs on GPUs along with distributed computing for scalability
• Contribute to tools and capabilities for model management and model performance monitoring
• Implement best engineering practices for scaling ML-powered features, enabling fast iteration and efficient experimentation with novel features
• Champion and own the ML infrastructure roadmap, in collaboration with Data Science and other platform teams
• Develop robust end-to-end production pipelines including a Human-in-the-Loop component to boost quality

What you'll need

• Bachelor's or Master's in Computer Science or Maths/Stats from a reputed college
• 7+ years of experience in solving machine learning engineering problems
• Prior experience deploying large-scale machine learning models to production, in both batch and real-time setups
• Experience with distributed computing frameworks like Spark / Map-Reduce etc.
• Cloud experience with any one provider (AWS / GCP / Azure)
• Experience with Infrastructure-as-code tools like Terraform
• Experience and understanding of the entire machine learning pipeline from data ingestion to production
• Experience with machine learning operations, software engineering, and architecture
• Experience architecting and building AI pipelines that support productionization of ML models
• Strong programming skills in a scientific computing language such as Python, SQL
• Experience using frameworks for machine learning and data science like scikit-learn, pandas, NumPy
• Ability to take successful, complex research ideas from experimentation to production
• Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams
• Good depth and breadth in machine learning (theory and practice), optimization methods, data mining, statistics and linear algebra

Nice to have

• Experience with Databricks
• Experience working with ML tools such as TensorFlow, Keras, and PyTorch

Details

• Location: Bengaluru, Karnataka, India