Senior Machine Learning Engineer

This is a fully remote position, open to applicants in Texas.

📋 Description

• Designing, constructing, deploying, and enhancing comprehensive AI & ML systems.

• The primary focus will be on agentic capabilities, agent-to-agent (A2A) protocols, demand modeling and forecasting, optimization, and product relationships.

• Expanding new functionalities on the Science roadmap.

• Engaging in full-stack technology, ranging from prototyping to production-ready software.

• Collaborating with product teams, engineers, and data scientists to convert concepts into innovative products, services, and features.

• Promoting and advocating for the capabilities of the Science team.

⛳️ Requirements

• Bachelor's or Master’s degree in a STEM discipline, such as computer science.

• Proficient in Python, SQL, and agentic frameworks like ADK or LangChain.

• Skilled in agentic development concepts, including Skills, Tools, Callbacks, code execution, token caching, compaction, and multi-agent orchestration.

• Experience in exposing agentic systems using MCP or A2A frameworks.

• Familiarity with cloud-native environments such as GCP (BQ, Cloud Run, GKE, etc.) or AWS.

• Proven track record of developing and scaling AI/ML systems within software products and production settings.

• Broader software development expertise (backend/frontend, data engineering, APIs, system design, etc.).

• Experience in building scalable agentic systems in a production environment.

• Comfortable with LLM-based development platforms like Claude or Codex.

• Exceptional algorithmic problem-solving abilities and an analytical approach.

• A proactive, security-conscious mindset.

• Experience with large-scale, high-performance systems and comprehensive software development life-cycle experience (CI/CD, etc.).

• Enthusiastic about tackling challenging technical problems and exhibiting natural intellectual curiosity.

• Aims to instigate change and influence others through clear and effective communication.

🏝️ Benefits

• Industry-leading training and development opportunities.

• An inclusive culture.

• A competitive total rewards package.

• Discretionary incentive compensation based on individual achievements.