Senior ML Engineer, Applied Machine Learning

Position Overview

• Location Type: Fully Remote, USA
• Job Type: [Employment Type Not Specified]
• Salary: [Salary Not Specified]

Trase Systems is seeking a Senior Machine Learning Engineer passionate about developing and refining machine learning systems, architecting and optimizing ML models that drive innovation and results. This role is instrumental in advancing Trase's ML systems, focusing on model training, pipeline development, and the fine-tuning of large language models (LLMs) to ensure peak performance.

About Us

Red Cell Partners is an incubation firm building and investing in rapidly scalable technology-led companies that are bringing revolutionary advancements to market in three distinct practice areas: healthcare, cyber, and national security. United by a shared sense of duty and deep belief in the power of innovation, Red Cell is developing powerful tools and solutions to address our Nation’s most pressing problems.

About Trase

Co-founded in 2023 by Joe Laws and Grant Verstandig, Trase Systems is AI, Uncomplicated. Trase empowers enterprise leaders to harness the full potential of AI without the associated complexity and risks. We are an end-to-end solution for deploying, managing, and optimizing AI in the enterprise. Our platform specializes in bridging the “last mile” of AI adoption, unlocking AI's full potential while driving efficiency and significant cost savings.

Responsibilities

• Architect, Build, and Optimize ML Systems: Develop and deploy robust ML models that deliver high-impact results for real-world applications.
• Training Pipeline Development: Design and implement efficient, scalable pipelines to train and retrain ML models, ensuring they meet business needs.
• Fine-Tuning Large Language Models (LLMs): Continuously fine-tune LLMs to align with specific enterprise requirements, enhancing accuracy, relevance, and performance.
• Feedback Systems Design: Implement and refine feedback loops to iteratively improve the effectiveness of ML models over time.
• Cross-Functional Collaboration: Work closely with product and business teams to understand and translate requirements into ML solutions that provide tangible outcomes.
• Stay Current with ML Advancements: Keep up with the latest in ML research and best practices, applying insights to our ML infrastructure to ensure it remains at the cutting edge.
• Mentorship and Knowledge Sharing: Guide and mentor junior team members, fostering a culture of continuous improvement and technical growth.
• Technical Communication: Clearly and effectively communicate ML methodologies, results, and insights to non-technical stakeholders.

Requirements

• ML Systems Expertise: Proven experience in developing, optimizing, and deploying ML systems in production environments.
• Model Training and Pipeline Mastery: Strong background in building and managing end-to-end training pipelines for ML models.
• LLM Fine-Tuning: Extensive knowledge and hands-on experience in fine-tuning large language models for specific use cases and optimizing them for targeted outcomes.
• Framework Proficiency: Skilled in ML frameworks such as TensorFlow, PyTorch, or similar tools used in ML model development.
• Programming Skills: Proficient in Python with a focus on writing efficient, clean, and maintainable code for ML applications.
• Clear Communicator: Ability to distill complex ML concepts for both technical and non-technical audiences.
• Educational Background: Bachelor’s or Master’s degree in Machine Learning, Computer Science, Data Engineering, or a related field.
• Impactful ML Solutions: A track record of delivering and implementing machine learning solutions that have successfully driven value in real-world applications.

Benefits

• Competitive salary and performance-based bonuses.
• Comprehensive health and w[enefits not fully specified]