Senior ML Engineer / Data Scientist

Quantori; Glasgow; Hybrid; GBP 80,000 - 100,000; Full time

Job summary

A leading technology company in Glasgow seeks a skilled Senior ML Engineer to architect multi-agent systems for biomedical data retrieval and interpretation. You will develop and tune machine learning models, communicate findings to clinical researchers, and ensure workflow compatibility with tools and APIs. This position offers competitive compensation, flexible working hours, and opportunities for continuous education and mentoring, alongside strong healthcare benefits.

Benefits

Competitive compensation

Remote or office work

Flexible working hours

Healthcare benefits

Continuous education programs

Mentoring opportunities

Certifications paid by the company

Qualifications

• Proficiency in Python and data science frameworks.
• Experience with common ML frameworks.
• Experience with Multi-agent systems and API integration.
• Upper-Intermediate English level required.
• Ability to mentor and communicate effectively.

Responsibilities

• Architect multi-agent systems for biomedical applications.
• Develop and tune ML models for data interpretation.
• Communicate findings to clinical researchers.
• Integrate tools and ensure workflow compatibility.
• Diagnose reasoning gaps and refine logic.

Skills

Python programming

ML frameworks (PyTorch, Keras)

LLM agents

Multi-agent system architecture

MCP tool integration

API design

Error handling and debugging

Modular system design

English proficiency

Client communication

Mentorship

Quick learner with adaptability

Job description

We are looking for a skilled and motivated Senior ML Engineer to join our dynamic team at Quantori. This position requires architecting and integrating multi-agent systems to support biomedical data retrieval and interpretation for target ideation, focusing on agentic workflows and tool compatibility. The role will be supported by an internal data scientist, e.g., coding tasks, data exploration, testing, etc.

Location: USA, UK, EU

Responsibilities

• Architect multi-agent systems (supervisor, router, reasoning flow)
• Develop / tune ML models
• Ensure reproducibility, documentation
• Communicate ML findings to clinical research
• Integrate MCP server (potential) / other tools; ensure workflow compatibility
• Develop agent decision policies
• Diagnose reasoning gaps, refine routing logic

What we expect

• Proficiency in Python programming and experience with Python data science frameworks
• Familiarity with common ML frameworks (e.g., PyTorch, Keras) and libraries (e.g., NumPy, scikit-learn)
• Experience with LLM agents including tool using and reasoning, for instance, the combination of RAG solution and code interpreter
• Experience with Multi-agent system architecture (e.g., LangGraph, ToolUniverse)
• Experience with MCP tool integration and orchestration
• Experience with API design and integration
• Experience with tool wrapping and interoperability
• Experience with Error handling and debugging (agentic workflows, logs)
• Experience with Modular system design, performance constraints
• Upper-Intermediate or higher level of English proficiency
• Ability to work with external clients and strong communication skills, including presenting in webinars and conferences
• Ability to mentor team members and assist in their professional development
• Quick learner with the ability to adapt to new technologies, frameworks, and algorithms
• Preferred Skills : Bioinformatics / drug development lifecycle domain knowledge
• Knowledge Graphs (cypher)
• Background in clinical development, health analytics, biostatistics
• Real-world data experience (EHR, claims) and amiliarity with medical coding systems (ICD-10, Snomed, RxNorm, CPT, NDC)

Preferred Skills

• Bioinformatics / drug development lifecycle domain knowledge
• Knowledge Graphs (cypher)
• Background in clinical development, health analytics, biostatistics
• Real-world data experience (EHR, claims) and amiliarity with medical coding systems (ICD-10, Snomed, RxNorm, CPT, NDC)

We offer

• Competitive compensation
• Remote or office work
• Flexible working hours
• Healthcare benefits : medical insurance and paid sick leave
• Continuous education, mentoring, and professional development programs
• A team with excellent tech expertise
• Certifications paid by the company