Job
Description
Dreaming big is in our DNA Its who we are as a company Its our culture Its our heritage And more than ever, its our future A future where were always looking forward Always serving up new ways to meet lifes moments A future where we keep dreaming bigger We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential The power we create together when we combine your strengths with ours is unstoppable Are you ready to join a team that dreams as big as you do AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology The teams are transforming Operations through Tech and Analytics, Do You Dream Big We Need You, Job Description Job Title: Senior ML Engineer Location: Bangalore Reporting to: Director Data Analytics Purpose of the role Anheuser-Busch InBev (AB InBev)s Supply Analytics is responsible for building competitive differentiated solutions that enhance brewery efficiency through data-driven insights We optimize processes, reduce waste, and improve productivity by leveraging advanced analytics and AI-driven solutions, Senior MLE, will be responsible for the end-to-end deployment of machine learning models on edge devices You will take ownership of all aspects of edge deployment, including model optimization, scaling complexities, containerization, and infrastructure management, ensuring high availability and performance, Key tasks & accountabilities Lead the entire edge deployment lifecycle, from model training to deployment and monitoring on edge devices Develop, and maintain a scalable Edge ML pipeline that enables real-time analytics at brewery sites, Optimize and containerize models using Portainer, Docker, and Azure Container Registry (ACR) to ensure efficient execution in constrained edge environments, Own and manage the GitHub repository, ensuring structured, well-documented, and modularized code for seamless deployments, Establish robust CI/CD pipelines for continuous integration and deployment of models and services, Implement logging, monitoring, and alerting for deployed models to ensure reliability and quick failure recovery Ensure compliance with security and governance best practices for data and model deployment in edge environments, Document the thought process & create artifacts on team repo/wiki that can be used to share with business & engineering for sign off, Review code quality and design developed by the peers, Significantly improve the performance & reliability of our code that creates high quality & reproducible results, Develop internal tools/utils that improve productivity of entire team, Collaborate with other team members to advance the teams ability to ship high quality code fast! Mentor/coach junior team members to continuously upskill them, Maintain basic developer hygiene that includes but not limited to, writing tests, using loggers, readme to name a few, Qualifications, Experience, Skills Level of educational attainment required (1 or more of the following) Academic degree in, but not limited to, Bachelors or master's in computer application, Computer science, or any engineering discipline, Previous Work Experience 5+ years of real-world experience to develop scalable & high-quality ML models, Strong problem-solving skills with an owners mindset?proactively identifying and resolving bottlenecks, Technical Skills Required Proficiency with pandas, NumPy, SciPy, scikit-learn, stats models, TensorFlow, Good understanding of statistical computing, parallel processing, Experience with advanced TensorFlow distributed, NumPy, joblib, Good understanding of memory management & parallel processing in python, Profiling & optimization of production code, Strong at Python coding Exposure to working in IDEs such as VSC or PyCharm, Experience in code versioning using Git, maintaining modularized code base for multiple deployments, Experience in working in an Agile environment, In depth understand of data bricks (Workflows, cluster creation, repo management), In depth understanding of machine learning solution in Azure cloud, Best practices in coding standards, unit testing, and automation, Proficiency in Docker, Kubernetes, Portainer, and container orchestration for edge computing, Other Skills Required Experience in real-time analytics and edge AI deployments Exposure to DevOps practices, including infrastructure automation and monitoring tools Contributions to OSS or Stack overflow, And above all of this, an undying love for beer! We dream big to create future with more cheers
