Senior Machine Learning Researcher, Applied Machine Learning

Summary

Join Trase Systems as a Senior ML Researcher and lead innovations in machine learning model architecture, fine-tuning, and continuous improvement. Drive research, development, and optimization of machine learning models to solve real-world business problems through advanced ML techniques.

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

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

Benefits

• 100% employer paid, comprehensive health care including medical, dental, and vision for you and your family
• Paid maternity and paternity for 14 weeks at employees' normal pay
• Unlimited PTO, with management approval with all Federal holidays observed
• Opportunities for professional development and continued learning
• Occasional travel to our offices in Washington D.C or alternative locations to collaborate with your team in person
• Optional 401K and FSA available
• Ability to work fully remote within the United States