Principal Applied ML Researcher – Agentic Systems, Applied AI Platform
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Job Description
Define and drive ML and LLM strategy for Trase’s agentic execution platform. Handle research-to-production lifecycle and ensure ML systems are reliable and effective.
Responsibilities:
- 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.
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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