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AI, Uncomplicated.
Principal Applied ML Researcher – Agentic Systems, Applied AI Platform
Location
Virginia + 1 moreAll locations: Virginia | Washington
Posted
60 days ago
Salary
$230K - $300K / year
Seniority
Lead
Job Description
Principal Applied ML Researcher – Agentic Systems, Applied AI Platform
Trase
• Drive technical breakthroughs in agentic systems, applied ML infrastructure, and LLM-based applications. • Define and evolve the ML/LLM strategy and technology roadmap in alignment with product development. • Act as a principal technical authority, making high-impact architectural and modeling decisions across teams. • Develop prototypes for key technologies to validate new approaches and de-risk system design. • Own the full lifecycle from research and experimentation through production deployment, monitoring, and iteration. • Translate advances in ML into scalable, production-grade systems with measurable impact. • Design how LLMs operate within agent workflows, tool use, and multi-step reasoning and long-lived execution. • Implement and refine prompting strategies, multi-agent orchestration, memory management, and human-in-the-loop controls for safety and reliability. • Establish patterns for planning, decision-making, and tool orchestration within complex systems. • Own end-to-end quality evaluation of ML-powered systems, including defining metrics, benchmarks, and testing frameworks. • Establish evaluation systems that connect model performance to task success and system-level outcomes. • Ensure systems behave predictably, safely, and reliably in production through monitoring, regression testing, and robust failure handling. • Contribute to the design of ML systems supporting the full lifecycle, including training, fine-tuning, evaluation, deployment, and monitoring. • Drive architecture decisions across model serving, routing, orchestration, and latency and cost optimization. • Work across infrastructure layers, including cloud and containerized systems, to ensure scalable and efficient deployment. • Build and deploy enterprise-grade AI systems used by global customers in production environments. • Design systems that operate reliably in regulated and constrained settings, including on-premise, air-gapped, and secure cloud environments. • Ensure systems are auditable, explainable, and compliant with regulatory and organizational requirements. • Write technical reports and design documents summarizing R&D progress, system behavior, and key decisions. • Communicate complex ML concepts and tradeoffs clearly to both technical and non-technical stakeholders. • Drive alignment across research, engineering, and product through strong technical leadership. • Mentor junior and senior engineers and researchers, raising the bar for ML rigor and system-level thinking. • Establish and propagate best practices for ML system design, evaluation, and reliability across the organization. • Influence technical direction beyond immediate teams through high-impact, cross-functional work.
Job Requirements
- 12–15+ years of experience in machine learning, including building and deploying applied ML systems in production environments.
- Strong programming skills in Python, with experience in Java, C++, or related languages in systems contexts.
- Deep expertise in at least one major ML domain, such as LLMs and generative AI, NLP or multimodal systems, deep learning, or graph learning.
- Hands-on experience with prompt engineering, multi-agent orchestration, tool integration via APIs, memory management, and human-in-the-loop system design.
- Proven experience building and shipping enterprise-grade AI systems, including GenAI, LLM, or agent-based applications at scale.
- Experience designing and implementing evaluation frameworks, including metrics, benchmarks, and testing systems.
- Strong understanding of ML system behavior in production, including reliability, latency, cost tradeoffs, and failure modes.
- Experience deploying ML systems in regulated or constrained environments and familiarity with modern ML infrastructure such as cloud platforms and containerized systems.
- Demonstrated ability to lead technical direction across teams and drive systems from concept to production impact.
Benefits
- Career track opportunity with potential for rapid advancement with strong performance as the firm grows
- 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.
- Opportunities for professional development and continued learning.
- Optional 401K, FSA, and equity incentives available.
- Mental health benefits are available through Tara Mind.
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