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Senior Machine Learning Engineer

  • On-site
    • Palo Alto, California, United States
  • Engineering

Join Trustero as a Sr ML Engineer! Focus on tuning ML models and leveraging LLMs for reasoning. Collaborate with engineering teams to enhance AI-driven compliance solutions. In-office, Palo Alto, CA.

Job description

About Trustero

Trustero is an advanced AI application, purpose-built for the Security and Compliance vertical. Our patented AI agents can accurately and consistently do the most time-consuming jobs in Governance, Risk, and Compliance, like perform gap analysis, provide remediation guidance, questionnaire automation, evidence collection + mapping, and more, saving companies hundreds-of-thousands of dollars and returning 100s of valuable working hours each month.


Role Overview

As a Senior Machine Learning Engineer at Trustero, you will play a crucial role in tuning and optimizing machine learning models, with a focus on leveraging large language models (LLMs) for reasoning and decision-making processes. This position focuses purely on machine learning and engineering, without the typical data science responsibilities. You will work closely with our engineering team to implement cutting-edge ML techniques that enhance the intelligence and performance of our compliance platform.

The ideal candidate enjoys working with advanced machine learning models and has a passion for applying LLMs in practical, impactful ways.


Key Responsibilities

  • Model Tuning & Optimization
    • Focus on tuning existing machine learning models to improve performance, accuracy, and scalability.

    • Apply advanced optimization techniques to ensure models are robust, efficient, and production-ready.

    • Work with large language models (LLMs) to implement reasoning and decision-making functionalities into Trustero’s platform.

  • LLM Integration & Reasoning
    • Develop techniques to leverage LLMs for reasoning, including automated decision-making processes and context understanding.

    • Integrate LLM-based solutions into the core product to enhance user experience and streamline compliance workflows.

  • Collaboration & Engineering
    • Collaborate with the engineering team to integrate machine learning solutions into our software infrastructure, ensuring compatibility and scalability.

    • Partner with product managers and engineers to ensure ML models align with the product vision and deliver tangible value to users.

    • Conduct code reviews, write clean, maintainable code, and follow best practices in machine learning engineering.

  • Continuous Improvement
    • Continuously experiment with new ML techniques and frameworks, particularly those related to LLMs and other emerging technologies.

    • Monitor and assess the performance of ML systems in production, iterating on solutions as needed to ensure high reliability.

Job requirements

  • 5+ years of experience in machine learning engineering, with a strong focus on tuning models and applying advanced ML techniques.
  • Bachelor’s degree in Computer Science, Software Engineering, or a related field; advanced degrees are a plus.

  • Proven experience working with large language models (LLMs) and applying them to reasoning and decision-making problems.

  • Expertise in machine learning frameworks (e.g., PyTorch, LlamaIndex, LangChain) and strong programming skills in Python or similar languages.

  • Strong understanding of cloud platforms like AWS, GCP, or Azure for scaling and deploying machine learning solutions.

  • Experience with model tuning, optimization, and performance monitoring in production environments.

  • Excellent collaboration and communication skills, with the ability to work cross-functionally with engineering teams.

  • Strong problem-solving skills, capable of navigating complex technical challenges in a fast-paced environment.


Preferred Qualifications

  • Hands-on experience with NLP and techniques for leveraging LLMs in enterprise applications.

  • Familiarity with compliance, governance, or security-related platforms.

  • Experience with microservices architecture, DevOps, and containerization tools like Docker and Kubernetes.

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