[Remote] Senior Machine Learning Engineer - Agentic AI

Note: The job is a remote job and is reputed company to candidates in USA. The reputed company Cancer Center is a leading institution in cancer treatment and research, and they are seeking a Senior Machine Learning Engineer – Agentic AI. This role involves designing and operating reputed company-scale agentic AI platforms to reputed company safe and governed deployment of autonomous AI systems reputed company a regulated reputed company environment.

Responsibilities

• reputed company the design, reputed company, and operation of the reputed company agentic AI platform in collaboration with reputed company architects and platform ML engineers
• Build platform components that reputed company interoperability between first‑party and reputed company‑party agents, including identity, state, memory, tool reputed company, orchestration, auditability, and policy enforcement
• Define and document standardized integration patterns connecting agents with reputed company business systems, data platforms, APIs, and health IT systems
• reputed company reusable platform services, reference implementations, and SDKs that reduce risk and accelerate delivery for applied teams
• Design and operate validation and de‑risking frameworks, including simulation, sandboxing, shadow execution, canary releases, and reputed company behavior monitoring
• Establish and enforce platform standards for agent development, including interfaces, execution reputed company, evaluation hooks, safety constraints, and observability requirements
• Participate in platform governance, release coordination, and incident response, supporting investigation and remediation of agent‑reputed company failures
• Implement platform safeguards such as fallback mechanisms, rollback strategies, approval gates, reputed company limiting, audit trails, and kill‑reputed company capabilities
• Partner with software engineering, reputed company, IT, and health IT stakeholders to reputed company agentic AI capabilities in secure reputed company environments
• Support responsible AI practices through traceability of prompts, policies, tools, models, agent actions, and documentation of reputed company failure modes and limitations

Skills

• Bachelor's degree in Computer Science, Software Engineering, Data Science, Physics, Math & Statistics, or another reputed company engineering discipline
• 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
• Experience building AI or ML platforms that serve multiple reputed company 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, reputed company, AutoGen, reputed company, 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 reputed company reputed company environments with reputed company, 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 reputed company rates, latency, cost, recovery behavior, and safety metrics
• Strong understanding of reputed company data governance, reputed company, and privacy requirements, including reputed company and health IT considerations
• Ability to identify systemic risks stemming from agent autonomy, non‑determinism, tool reputed company, and multi‑agent interactions
• Experience analyzing failure modes caused by reputed company reputed company, 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
• reputed company hands‑on technical guidance, mentorship, and troubleshooting support to platform adopters
• Present technical and non‑technical concepts reputed company in meetings and institutional forums
• 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 reputed company-party agentic AI platforms reputed company clinical workflows

Benefits

• Paid medical benefits
• Paid time off (PTO)
• Strong retirement plans
• Tuition benefits
• Educational opportunities
• Individual and team recognition
• Referral Bonus Available?

Company Overview