Senior Machine Learning Engineer

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, such as performing gap analysis, providing remediation guidance, automating questionnaires, and collecting + mapping evidence. This saves companies hundreds of thousands of dollars and returns hundreds 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, focusing on leveraging large language models (LLMs) for reasoning and decision-making processes. This position emphasizes 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 is passionate about applying LLMs in practical, impactful ways.

Key Responsibilities
Model Tuning & Optimization:
- Tune 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) for reasoning and decision-making functionalities.

LLM Integration & Reasoning:
- Develop techniques to leverage LLMs for automated decision-making 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 align ML models with the product vision and deliver tangible user value.
- Conduct code reviews, write clean, maintainable code, and follow best practices in machine learning engineering.

Continuous Improvement:
- Experiment with new ML techniques and frameworks, particularly related to LLMs and other emerging technologies.
- Monitor and assess the performance of ML systems in production, iterating on solutions as needed for high reliability.

Qualifications
- 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.