Full-Time

Senior ML Researcher

Applied Machine Learning, Security Clearance

Posted on 10/7/2025

Trase Systems

Trase Systems

11-50 employees

Platform for deploying autonomous enterprise AI

Compensation Overview

$175k - $225k/yr

+ Equity Incentives

McLean, VA, USA

In Person

Some travel is required.

Category
AI & Machine Learning (2)
,
Required Skills
Python
Tensorflow
Pytorch
Machine Learning
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 natural language processing 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.
  • Active Secret or Top Secret Clearance
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.

Trase Systems provides an enterprise AI platform that enables large organizations to deploy, manage, and optimize autonomous AI agents. It offers an end-to-end, model-agnostic solution with an agent builder, multi-agent orchestration, and full observability, designed to automate complex administrative workflows in regulated sectors such as healthcare, national security, and energy. The platform can run across cloud, on-premises, or air-gapped environments to support sensitive workloads, with SOC 2 and HIPAA compliance. Trase differentiates itself through a shared-savings business model (no upfront costs) and a focus on measurable efficiency gains from AI agents, lowering barriers to ROI while ensuring enterprise-grade governance and security. Its goal is to simplify AI adoption for large organizations by addressing the “last mile” of AI implementation and delivering practical, auditable automation at scale.

Company Size

11-50

Company Stage

N/A

Total Funding

N/A

Headquarters

N/A

Founded

2023

Simplify Jobs

Simplify's Take

What believers are saying

  • US Navy contract validates national security AI applications.
  • Duke Health partnership proves healthcare workflow automation value.
  • Red Cell Partners incubation leverages AI agent frontier advancements.

What critics are saying

  • DoD CDAO bans non-FedRAMP AI, disqualifying air-gapped deployments now.
  • OpenAI Swarm commoditizes orchestration, enabling internal builds immediately.
  • UiPath Pathmind acquisition undercuts healthcare savings with RPA scale.

What makes Trase Systems unique

  • Model-agnostic platform deploys AI agents in air-gapped systems.
  • Shared savings model charges only on efficiency gains achieved.
  • Automates healthcare workflows like prescription refills for Duke Health.

Help us improve and share your feedback! Did you find this helpful?

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Paid Sick Leave

Parental Leave

Unlimited Paid Time Off

Professional Development Budget

401(k) Retirement Plan

401(k) Company Match

Mental Health Support

Performance Bonus

Flexible Work Hours

Growth & Insights

Headcount

6 month growth

6%

1 year growth

4%

2 year growth

-4%
INACTIVE