Trustero, Inc.
Senior Machine Learning Engineer
Trustero, Inc., Palo Alto, California, United States, 94306
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.
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.
#J-18808-Ljbffr
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.
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.
#J-18808-Ljbffr