Senior Machine Learning Engineer - Agentic AI

Experience building AI or ML platforms that serve multiple downstream teams and production workloads.

Strong proficiency in Python and integration of modern ML frameworks (e.g., PyTorch) with large language models and agent systems.

Hands‑on experience with agentic AI frameworks such as LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, or equivalent.

Working knowledge of agentic AI protocols and interoperability standards (e.g., MCP, agent‑to‑agent communication, structured tool invocation).

Experience implementing planner‑executor loops, hierarchical agents, and multi‑agent coordination patterns.

Familiarity with workflow orchestration tools (Airflow, Prefect, Temporal) and distributed execution frameworks (Ray or equivalent).

Experience deploying containerized AI platforms using Kubernetes in enterprise cloud environments with lineage, auditability, and controlled promotion to production.

Ability to reason at the systems and platform level, balancing safety, performance, flexibility, and usability.

Experience designing quantitative evaluation strategies for agentic systems, including success rates, latency, cost, recovery behavior, and safety metrics.

Strong understanding of enterprise data governance, security, and privacy requirements, including healthcare and health IT considerations.

Ability to identify systemic risks stemming from agent autonomy, non‑determinism, tool access, and multi‑agent interactions.

Experience analyzing failure modes caused by prompt drift, model updates, tool changes, and cross‑system dependencies.

Collaborate effectively with architects, applied MLEs, data scientists, software engineers, and IT partners.

Produce clear documentation covering platform architecture, APIs, integration patterns, validation frameworks, and operational runbooks.

Communicate platform capabilities, risks, and limitations to leadership and partner teams.

Contribute to internal standards and shared practices that improve safety, scalability, and consistency of agentic AI development.

Provide hands‑on technical guidance, mentorship, and troubleshooting support to platform adopters.

Present technical and non‑technical concepts clearly in meetings and institutional forums.

Education Required: Bachelor's degree in Computer Science, Software Engineering, Data Science, Physics, Math & Statistics, or another related engineering discipline.

Preferred Education : Master’s degree or PHD with a concentration in Science, engineering, or related field.

Experience Required : Five years of experience in machine learning engineering, data science, data engineering, and/or software engineering. With Master's degree, three years’ experience required. With PhD, one year of experience required.

Preferred Experience:

Experience designing, deploying, and maintaining agentic AI systems that operate autonomously and collaboratively across distributed environments.

Experience in monitoring and troubleshooting autonomous agents post-deployment, including performance degradation, clinical incidents, model updates, or corrective actions.

Experience raising the technical bar for team members, such as establishing reproducibility practices, review standards, or shared patterns.

Experience technically evaluating third-party agentic AI platforms within clinical workflows.

The University of Texas MD Anderson Cancer Center offers excellent benefits , including medical, dental, paid time off , retirement , tuition benefits, educational opportunities, and individual and team recognition.

This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.

It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html

Requisition ID: 178303

Employment Status: Full-Time

Employee Status: Regular

Work Week: Days

Minimum Salary: US Dollar (USD) 146,500

Midpoint Salary: US Dollar (USD) 183,000

Maximum Salary : US Dollar (USD) 219,500

FLSA: exempt and not eligible for overtime pay

Fund Type: Hard

Work Location: Remote (within Texas only)

Pivotal Position: Yes

Referral Bonus Available?: Yes

Relocation Assistance Available?: Yes