Machine Learning Engineer

Aptos has an opening for an ML engineer to join our Bengaluru team. Aptos’ market-leading platform drives the world’s largest retailers in terms of their product pricing, promotion and merchandising decisions worldwide.  Over 33,000 retail locations and $200+B in annual revenue across grocery, drug, convenience, general merchandise, discount, sporting goods stores, fashion, and eCommerce sites optimize with Aptos’ solutions.

The Science team, within the Product Org, plays a central role at the company and is responsible for the different AI/ML solutions (modeling, forecasting, optimization, agentic AI etc) at Aptos. As an ML engineer on the Science team, you will get to be part of a skilled and diverse team while working with a mix of data scientists and engineers. You’ll not only have the opportunity to learn/use state-of-art machine learning techniques but also implement/roll-out modern engineering frameworks. 

If you’re someone who is ready to take on a challenge, drive change, and be part of an awesome team, this is the right role for you!

About the Role:

The ML engineer role is responsible for designing, building, deploying, and evolving the end-to-end AI/ML systems at Aptos’ (demand modeling and forecasting, optimization, AI, etc.) 

Who you are?

• You have a Bachelor's/Master’s degree in computer science, engineering, or related STEM field, or equivalent work experience
• Strong algorithmic problem-solving skills and an analytical mindset
• Development experience with one or more of the following, or another similar language: Python, C/C++, Java for minimum 1 year
• Familiarity with Machine Learning software such as Tensorflow, Pytorch, Scikit-Learn, Spark MLLib, etc.
• Familiarity with GenAI / LLM concepts such as agent frameworks, workflows, evaluation, RAG, prompting, fine-tuning, etc.
• Able to communicate, collaborate, and work effectively in a distributed team.
• Can think about and write high quality code and can demonstrate that capability, be it through job experience, schoolwork, or contributions to community projects.
• Complete course work/experience with Algorithms, Distributed Systems, Databases
• Solid understanding of software engineering concepts and methodologies
• Familiarity with software testing principles
• Enjoy tough technical challenges and are naturally intellectually curious
• Seek to drive change and influence others through clear and effective communication. 

What you’ll do?

• Work and interact with a diverse set of stakeholders in a cross-functional organization within an Agile environment.
• Perform research as required to specify and develop or enhance your product
• Work with product, engineers, and data scientists to translate ideas into new products, services and features
• Strengthen technical skills through mentorship and guidance from experienced engineers

We also look for

• Passion
• Initiative and a Pioneering Spirit
• Quality orientation
• Resourcefulness and application

Are you the person we’re looking for?

Big picture thinker with laser focus. You have a unique ability to see both the forest and the trees. It’s what sets you apart from the rest. You start with a good understanding of the broader strategy, zoom in to assess one particular aspect of that strategy, and then zoom back out to see how changes to that particular area will affect the broader process.

Expert relationship cultivator. Product managers think you’re a good partner -- because you are. Developers feel you respect their opinions -- because you do. You’re a true people person, a natural collaborator, and a highly sought-after resource.

Quality orientation. You have proven success at writing quality user stories and analysis deliverables through the application of established criteria like INVEST and SMART. Your work is thoughtful, timely and valuable to the team.

Resourcefulness and application. At Aptos, we have a pioneering spirit -- when we have questions, we find answers; when we’re faced with challenges, we find solutions. We turn to a variety of resources, including our own colleagues, our professional network, the Internet, articles and books -- whatever helps us get the job done. But it’s not just about using a variety of resources to gain knowledge -- it’s also about applying that knowledge to other areas of the job or business where it might make sense.