Applied Scientist, GenAI & ML Systems

RXinsider LTD.; Wilmington (MA); On-site; USD 175,000 - 216,000; Full time

Job summary

TraceLink in Wilmington, MA is seeking an Applied Scientist to lead GenAI and ML systems design and deployment. You will build, iterate, and ship production-grade multi-agent architectures in cloud environments, focusing on LLM/SLM optimization and agent coordination.

The role emphasizes hands-on work across model fine-tuning, RAG pipelines, and tool integration, with strong collaboration across platform and product engineering. A senior, production-focused ML background is expected.

Qualifications

• Extensive experience with multi-agent system design and production ML.
• Proven ability to translate requirements into architectures and metrics.
• Experience with LLM/SLM optimization and cloud deployment.
• Experience with vector databases and retrieval pipelines.
• Hands-on inference optimization and model routing.

Responsibilities

• Own building, shipping multi-agent systems from prototype to production.
• Develop production-quality orchestration, memory design, and context management.
• Lead context engineering for coordination across agents.
• Fine-tune and deploy SLM models for production usage.
• Build end-to-end RAG pipelines including embeddings and retrieval.
• Collaborate with engineering to ensure scalable, secure cloud-native solutions.

Skills

Context engineering

Fine-tuning SLMs

Advanced RAG

Vector DB retrieval

Production Python

Cloud deployment

Education

MS/PhD in CS/ML/NLP/Stats

Tools

Python

AWS/Azure/GCP

Docker

Kubernetes

Job description

Company overview:

TraceLink is the world's largest Agentic Business Network, enabling life sciences and healthcare companies to build and manage a scalable digital workforce of governed, no-code AI agents that execute and coordinate mission-critical supply chain operations alongside human teams. Powered by the Integrate-Once OPUS platform, TraceLink links more than 300,000 network participants, enabling multi-enterprise processes at global scale.

Founded in 2009 with the simple mission of protecting patients, today Tracelink has 5 global offices, over 800 employees and more than 1700 customers in over 60 countries around the world. Our expanding product suite continues to protect patients and now also enhances multi-enterprise collaboration through innovative new applications such as MINT.

Tracelink is recognized as an industry leader by Gartner and IDC, and for having a great company culture by Comparably.

Applied Scientist, GenAI & ML Systems

Location:

Wilmington, MA (US) - Fulltime Onsite

About The Role

We are hiring an Applied Scientist to lead the design and deployment of production-grade GenAI and ML systems with a strong emphasis on being hands-on. You will personally build, iterate, and ship systems focused on LLM/SLM optimization for agentic, multi-agent architectures in cloud environments.

This role is ideal for someone with deep expertise in one or more areas of LLM/SLM optimization for agent-based systems, and hands-on experience in designing, implementing, and operating large-scale multi-agent systems in the cloud.

Key Responsibilities

• Hands-on ownership of building and shipping multi-agent systems (planner/executor, tool-using agents, supervisor patterns, routing, role-based agents) from prototype to production.
• Write production-quality code for agent orchestration, tool integration, memory/state design, and context management.
• Lead context engineering strategies for multi-agent coordination: prompt design, state persistence, agent handoffs, grounding, constraints, and safety controls.
• Hands-on fine-tune and deploy SLM models for production usage: dataset creation, training workflows, evaluation, and inference serving.
• Build Advanced RAG pipelines end-to-end, including semantic search, embeddings, hybrid retrieval, and cross-encoder reranking.
• Implement evaluation frameworks for multi-agent systems covering quality, latency, cost, robustness, and failure mode detection.
• Collaborate with platform and product engineering to ensure solutions are cloud-native, secure, observable, and scalable (monitoring, logging, CI/CD).
• Optimize for cost and latency via model routing, caching, compression strategies, and inference efficiency improvements.
• Mentor peers through code reviews, architecture sessions, and hands-on technical leadership.

Required Knowledge & Experience

• Context engineering for complex multi-agent systems (prompt orchestration, tool calling, memory/state design, routing, constraint handling)
• Fine-tuning of SLMs and delivering them to production (training strategies, validation, deployment, monitoring, rollback readiness)
• Experience with Advanced RAG, semantic search, embeddings, and cross-encoders (retrieval tuning, chunking strategies, query rewriting/planning, reranking)
• Ability to translate ambiguous requirements into concrete architectures, metrics, and deliverables
• Hands-on inference optimization experience: quantization, distillation, batching, caching, model routing, speculative decoding
• Experience building retrieval systems at scale using vector DBs and search stacks
• Comfort working across the full lifecycle: research -> prototype -> A/B test -> production hardening

Preferred Qualifications

• Familiarity with enterprise constraints: privacy, security, data governance, permissions, auditability
• Experience designing and running GenAI observability: traces, prompt/versioning, tool call logging, feedback loops
• Strong ability to implement production-quality systems in Python (and/or adjacent backend languages)
• Proven experience deploying GenAI/ML systems in cloud environments (AWS/Azure/GCP)
• Experience with scalable inference and service operations: containers, APIs, observability, reliability practices
• MS/PhD in CS/ML/NLP/Stats (or equivalent applied experience building production systems)

TraceLink is committed to providing competitive compensation and benefits to all employees. This is the estimated base salary range for this role and should serve only as a guide. Final compensation offered may vary based on a variety of factors including but not limited to experience level, fit for the role, skills, domain knowledge, internal equity, budget, and location.

US Pay Range

$175,289.18-$215,588.58 USD

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