Sr. Machine Learning Engineer

Revionics, an Aptos Company • US TX Remote, TX

1d • Onsite

About The Position

Revionics (an Aptos company) has an opening for a Senior ML engineer to join our US team located in the Austin area. Revionics’ 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 Revionics’ solutions. The Science team, within the Product Org, plays a central role at the company and is responsible for the various AI & ML solutions (agentic systems, modeling, forecasting, optimization, etc). 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 and develop state-of-art AI & ML techniques but also implement/roll-out modern engineering frameworks. Members of the team are expected to own the full Science feature lifecycle from research & development to prototyping to production and support. 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 Revionics’ – agentic capabilities, agent-to-agent (A2A) protocol, demand modeling and forecasting, optimization, product relationships, etc. – with an initial focus on our agentic and A2A roadmap.

Requirements

• Bachelor's/Master’s degree in a STEM field such as computer science.
• Proficiency in Python, SQL, and agentic frameworks such as ADK or LangChain.
• Proficiency with agentic development concepts such as Skills, Tools, Callbacks, code execution, token caching, compaction, multi-agent orchestration etc.
• Experience exposing agentic systems using MCP or A2A frameworks.
• Experience working in cloud native environments like GCP (BQ, Cloud run, GKE etc) or AWS.
• Strong track record of developing and scaling AI/ML systems within software products and production systems.
• Broader software development skills (backend/frontend, data engineering, APIs, system design, etc).
• Experience building scalable agentic systems in production.
• Comfort with LLM-based development platforms such as Claude or Codex.
• Strong algorithmic problem-solving skills and an analytical mindset.
• Proactively security-conscious mindset.
• Experience with large scale, high-performance systems and full software development life-cycle experience (CI/CD etc.).
• Enjoys tough technical challenges and is naturally intellectually curious.
• Seeks to drive change and influence others through clear and effective communication.
• Big picture thinker with laser focus.
• Expert relationship cultivator.
• Quality orientation.
• Resourcefulness and application.

Nice To Haves

• Experience with modeling frameworks (e.g. Tensorflow, PyTorch, JAX).
• Experience with data orchestration tools such Airflow.
• Exposure to on the fly code execution for large files.
• Experience with data analysis / data science.
• Ability to translate research work into practical proofs of concept.

Responsibilities

• Build out new features on our Science roadmap: Agentic AI as we introduce new capabilities to our agent such as product relationships, rules management, and scenario optimization; A2A communication protocol; predictive and decision-making AI as we build out our unified forecasting and optimization capabilities; and our push to modernize legacy features and functionality.
• Work on full stack technology, from prototyping to production-ready software.
• Work with product, other engineers, and data scientists to translate ideas into new products, services and features.
• Expose and evangelize our Science team capabilities.

Benefits

• industry-leading training and development opportunities
• competitive total rewards package including a base salary determined based on the role, experience, skill set, and location.
• discretionary incentive compensation may be awarded in recognition of individual achievements and contributions.
• a range of benefits and programs to meet employee needs, based on eligibility.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior