Demand Forecasting is a core function of the supply chain driving replenishment, sourcing, capacity and transportation plans. Improved accuracy of demand forecasting will help enhance sales and customer experience while reducing operational cost and wastage to the tune of billions of dollars. Doing this at Walmarts scale makes it one of the largest and most challenging problems of its kind in the world while also being the most impactful.

Our team is enabling internal data science teams to build and optimize their forecasting workflows and provide forecasts across channels and geographies at scale. We are looking to hire ML engineers to help create an industry-leading ML Platform that democratizes data science, reduces time to market and enhances the accuracy and preciseness of Forecasting models across Walmart. We are looking for motivated engineers with a solid foundation for Machine Learning/ Deep Learning architecture service development experience.

Position Responsibilities:

Design and develop state-of-art ML model development and orchestration framework

Design optimal Model run-time instances to improve model tun-time, cut-down compute cost

Build ML tools and framework that accelerate Data science experimentation

Collaborate with Technical Product Managers to influence the scope, capabilities, and roadmap of ML Platform

Articulate and document best practices and design principles to mentor other developers

Research and evaluate new open-source technologies and frameworks to solve problems improve existing solutions

Articulate and present the business value of your product design to different stakeholders and user

Position Requirements:

Minimum qualifications:

BTech/BE or above in computer science,

8 years of software development experience, and 3 years of experience in Platform Architecture.

Exposure to any Machine Learning / Deep Learning platform – SageMaker, Azure ML workbench, Google AI Platform, H2O AI, etc.

Exposure to distributed machine learning frameworks – PyTorch, Dask, Spark ML, etc

Strong Java programming skills

Hands-on experience on Big data technologies – Spark, BigQuery, Hive, Airflow, Object Storage, etc.

Understanding of Machine Learning Model Lifecycle (dev, deploy, release, CI).

Ability to learn quickly and adapt to different platforms as per the need of the project.

Additional Qualifications:

Large scale distributed systems experience, including scalability and fault tolerance.

Detailed knowledge of object-oriented design, data structures, and algorithms.

Exposure to cloud infrastructures, such as Open Stack, Azure, GCP, or AWS

Excellent oral and written communication skills.