Senior ML Engineer: Agentic AI & Pricing Forecasting

Revionics, an Aptos Company; Austin (TX); Hybrid; USD 120,000 - 170,000; Full time

Job summary

Revionics, an Aptos company, is seeking a Senior ML Engineer in the Austin area to design, build, deploy, and evolve end-to-end AI and ML systems—agentic capabilities, A2A protocols, and forecasting/optimization. The role blends research, prototyping and production support within the Science team of the Product Org.

You’ll work with data scientists and engineers to scale AI/ML in production, leverage cloud platforms (GCP/AWS), and pursue state-of-the-art techniques while driving impact for

Qualifications

• Bachelor's or Master's degree in a STEM field such as computer science.
• Proficiency in Python, SQL, and agentic frameworks such as ADK or LangChain.
• Experience exposing agentic systems using MCP or A2A frameworks.
• Experience with cloud native environments like GCP or AWS.
• Strong track record of developing and scaling AI/ML systems within software products.

Responsibilities

• Build out features on the Science roadmap including agentic AI capabilities and A2A protocol.
• Develop full-stack features from prototyping to production-ready software.
• Collaborate with product, engineers and data scientists to translate ideas into new products and services.
• Evangelize and showcase Science capabilities to stakeholders.

Skills

Python

SQL

agentic frameworks

cloud platforms

AI/ML systems

CI/CD

LLM platforms

problem solving

communication

multi-agent orchestration

Education

Bachelor's/Master’s in STEM

Tools

ADK

LangChain

GCP

AWS

TensorFlow/PyTorch/JAX

Job description

Revionics, an Aptos company, is seeking a Senior ML Engineer in the Austin area to design, build, deploy, and evolve end-to-end AI and ML systems—agentic capabilities, A2A protocols, and forecasting/optimization. The role blends research, prototyping and production support within the Science team of the Product Org.

You’ll work with data scientists and engineers to scale AI/ML in production, leverage cloud platforms (GCP/AWS), and pursue state-of-the-art techniques while driving impact for