Gentoro | Senior ML Engineer

Palm Venture Studios; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Gentoro in San Francisco is seeking a visionary Senior ML Engineer to bridge architecture and hands-on delivery, focusing on simplifying enterprise AI agent integration. You will define standards for platform scalability and cross-application interaction.

You will design multi-agent systems, build observability stacks with OpenTelemetry, enforce safety mechanisms to reduce hallucinations, and drive end-to-end reliability and performance in live environments.

Qualifications

• 5+ years of senior engineering experience at fast-paced tech startups.
• 2+ years of ML experience, including training or fine-tuning LLMs and embeddings.
• Proficiency in agent orchestration and memory-augmented systems.
• Experience using feedback loops to improve ML systems.
• Ability to thrive in startup ambiguity while maintaining enterprise-grade discipline.
• Demonstrated impact as a force multiplier for a technical team.
• Committed to practical, production-ready AI solutions.

Responsibilities

• Design and implement multi-agent systems and orchestration layers.
• Build and operate observability stacks (OpenTelemetry) to monitor reasoning paths, tool usage and performance.
• Develop and enforce technical safety mechanisms to mitigate hallucinations and biases.
• Create visualizations to convey behavior of agentic systems.
• Implement fallback mechanisms, HITL checkpoints, and automated recovery for failures.
• Apply best practices for LLMOps, monitoring, and performance tuning in live environments.
• Automate SDLC, CI/CD pipelines, elevate QA, and develop incident response protocols.

Skills

Senior engineering

ML

LLM models

Agent orchestration

Memory-augmented systems

Feedback loops

Startup discipline

Job description

About Us

Gentoro was founded by a team with deep experience in enterprise infrastructure and AI, with leadership roots at companies including Splunk, WebLogic, and Asurion. Gentoro helps organizations simplify AI integration into real-world systems, with the observability, manageability, and security required for production deployments. As agentic workflows shift from experimentation to real execution, Gentoro helps teams enforce governance, maintain auditability, and deliver reliable outcomes at scale.

About The Role

We are looking for a visionary Senior ML Engineer who will bridge the gap between high-level architecture and hands-on execution, specifically focusing on simplifying enterprise integration for AI agents. As a key hire during our current growth phase, you will define the standards for how our platform scales and interacts with other enterprise applications.

What You’ll Do

• Design and implement multi-agent systems and orchestration layers
• Build and operate observability stacks (e.g., OpenTelemetry) to monitor agent reasoning paths, tool usage, and performance in real-time
• Develop and enforce technical safety mechanisms—such as input/output filtering and behavioral boundaries—to mitigate risks like hallucinations, prompt injections, and bias
• Build visualizations to convey interesting behavior of agentic systems
• Implement fallback mechanisms, human-in-the-loop (HITL) checkpoints, and automated recovery for agentic failures
• Implement best practices for LLMOps, monitoring, and performance tuning of AI models in live environments
• Automate SDLC processes and CI/CD pipelines, elevate QA standards, and develop incident response protocols to enable high velocity, availability and reliability of our platform

Who You Are

• You thrive in the \"ambiguity phase\" of a startup but build with the discipline of an enterprise-grade engineer.
• You are a \"force multiplier\" who elevates the technical bar for the entire team.
• You are obsessed with the practical application of AI, moving beyond demos to create reliable, production-hardened products
• You have a high-confidence, low-ego mindset

Requirements

• 5+ years of senior engineering experience at a fast-paced, high-growth technology startup that has successfully scaled from early stage through Series A/B funding (or equivalent growth phase)
• 2+ years of ML, specifically training or fine-tuning LLM models, embeddings; building clustering models; utilizing evaluation frameworks to quantify performance
• Proficiency in agent orchestration and memory-augmented systems.
• Experience using feedback loops to continuously improve ML systems
• Thrives in startup ambiguity while maintaining the discipline of an enterprise-grade engineer
• Acts as a force multiplier who elevates the technical bar for the entire team
• Obsessed with practical application of AI systems and capable of building enterprise solutions that solve real-world customer problems