Trinity Life Sciences
Website:
trinitylifesciences.com
Job details:
We're committed to bringing passion and customer focus to the business.
Position Responsibilities
- Architect and deliver end-to-end agentic AI and ML systems — from data pipeline through to production deployment — for both client projects and internal platform development
- Build and iterate on agentic AI systems for document intelligence, knowledge extraction, quantitative reasoning, and decision support in life sciences contexts
- Implement scalable, production-ready solutions leveraging LLMs, prompt engineering, RAG pipelines, search frameworks, and multi-modal GenAI capabilities
- Translate ambiguous, fast-moving business and client requirements into working agentic AI prototypes and production-ready systems with minimal overhead
- Collaborate with product managers and designers to transition prototypes into scalable product features
- Contribute to engineering best practices, documentation, and shared tooling; identify and formalize patentable approaches where applicable
Qualifications
- 8+ years of experience in ML/AI research and engineering, with demonstrated end-to-end production deployments
- PhD in Computer Science, Machine Learning, Statistics, or a related quantitative discipline (or equivalent depth demonstrated through publications, patents, or production systems)
- Deep hands-on expertise in agentic AI system design
- Strong proficiency in Python and modern ML frameworks: PyTorch, TensorFlow, HuggingFace
- Experience building and operating large-scale distributed ML pipelines (e.g., PySpark, Ray, or equivalent)
- Strong grounding in deep learning architectures — Transformers, ViTs, CNNs — and the mathematical foundations underlying them
- Strong communication abilities and comfort engaging directly with non-technical stakeholders
- Ability to work independently in dynamic environments
Preferred
- Experience building enterprise agentic AI systems
- Comfort and familiarity with agentic AI coding tools (e.g., ClaudeCode)
- Prior exposure to life sciences, healthcare, or enterprise analytics domains
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