Senior ML Researcher, Applied Machine Learning

Location: Fully Remote, USA

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. Trase is at the forefront of AI Agent innovation, topping the Hugging Face GAIA Leaderboard for Generalized AI Assistants, ahead of industry giants such as Google, Meta, Microsoft, and OpenAI. We are leveraging our cutting-edge technologies to develop mission-critical agentic applications in complex industries such as Healthcare, Oil & Gas, and National Security. 

About the Role

Are you passionate about advancing machine learning through cutting-edge research? Do you thrive in optimizing and fine-tuning machine learning models, especially language models, to address complex business challenges? If so, we have an exciting opportunity for you as a Senior ML Researcher focused on applied ML.

In this role, you will spearhead innovations in machine learning model architecture, fine-tuning, and continuous improvement. This role emphasizes the exploration and development of research-based ML methodologies to optimize model performance and ensure our systems are both robust and adaptable to enterprise needs.

Responsibilities:

• Lead ML Research and Development: Drive the research, development, and optimization of machine learning models, focusing on solving real-world business problems through advanced ML techniques.
• Architect Novel Training and Fine-Tuning Methodologies: Design, implement, and iterate on advanced training protocols, fine-tuning processes, and optimization strategies, particularly for Language Models (LLMs).
• Evaluate Model Performance and Innovation: Develop and refine techniques for assessing and enhancing the effectiveness of ML models, focusing on accuracy, scalability, and adaptability to dynamic enterprise requirements.
• Feedback System Design for Continuous Learning: Create systems that incorporate user and system feedback to iteratively improve model performance over time.
• Cross-Functional Collaboration: Work closely with product teams and domain experts to translate business needs into research questions and actionable ML strategies.
• Stay Current on ML Advancements: Actively monitor the latest research in ML and NLP, integrating cutting-edge practices and methodologies into our development pipeline.
• Mentor and Guide Team Members: Provide technical guidance to junior researchers, fostering a culture of continuous learning, experimentation, and research-driven development.

Requirements:

• Expertise in ML Model Training and Optimization: Proven experience with ML research, including designing and evaluating novel training methodologies, model architectures, and optimization techniques.
• Deep Knowledge of Language Model Fine-Tuning: Demonstrated proficiency in customizing and fine-tuning language models to meet specific use cases, with experience in models such as GPT, BERT, or similar frameworks.
• Proficiency in ML Frameworks: Strong understanding of machine learning and NLP frameworks like TensorFlow, PyTorch, or similar, with the ability to design and implement custom model architectures.
• Programming Skills: Proficiency in Python with an emphasis on writing efficient, maintainable, and scalable code.
• Research Communication Skills: Ability to present complex technical concepts to both technical and non-technical stakeholders, highlighting the business impact of ML innovations.
• Educational Background: A Master’s or PhD in Computer Science, Machine Learning, or a related field, with a focus on ML research.
• Impactful ML Solution Delivery: Proven track record of delivering ML solutions that have made significant real-world impact, ideally within an enterprise or production setting.

Benefits: 

• Competitive salary and performance-based bonuses.
• Comprehensive health and wellness benefits package.
• Flexible work hours.
• Opportunities for professional development and continued learning.
• Collaborative and inclusive work environment.

Some travel is required.

If you want to be on the cutting edge of technology, building AI solutions for the future, and are up for a challenge, let’s talk!

Salary Range: $175,000-$225,000. This represents the typical salary range for this position based on experience, skills, and other factors.

#LI-RCP