As Chief Technology Officer at E184, you will transform complex, fragmented scientific processes into intelligent, automated, and trustworthy workflows. You will design and implement orchestrated, end-to-end systems connecting laboratory devices, APIs, datasets, and AI models to accelerate scientific discovery across domains like genomics and neuroscience.
What You'll Do
- Immerse yourself in how science happens at E184, from wet/dry lab operations to imaging pipelines and experimental data flows.
- Identify high-impact opportunities where AI, automation, and robotics can eliminate repetitive work in sample processing, imaging, cell culture screening, and experimental execution.
- Design and implement orchestrated, end-to-end workflows that connect laboratory devices, APIs, datasets, and AI models into coherent systems with built-in monitoring, traceability, and reliability.
- Blend large language models and other advanced architectures with live scientific data to enable systems that reason with real context and adapt in real time.
- Establish a unified foundation for data standards, metadata schemas, experiment tracking, versioning, access control, audit trails, and security.
- Stay hands-on building conversational agents and intelligent bots that take actions, understand nuance, and actively assist scientific teams.
- Collaborate closely with scientists, engineers, and operators to translate complex research needs into AI-powered systems that respect governance and build trust in data.
What We're Looking For
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 3+ years of hands-on experience building and deploying AI/ML systems or infrastructure in research-critical environments.
- Strong experience using LangChain/LangGraph for building LLM applications.
- Deep knowledge of vector databases (FAISS, PGVector, Qdrant) and RAG architectures for scientific knowledge retrieval and question-answering systems.
- Proficiency in Python, FastAPI, and key ML frameworks (Transformers, PyTorch, TensorFlow).
- Proven ability in advanced prompt engineering techniques.
- Hands-on approach and experience setting up integration of multiple solutions from scratch. You build systems yourself, end-to-end, writing code, training models, deploying systems, and keeping them running.
Nice to Have
- Experience with supporting new processes, products, operations, labs, manufacturing sites, etc.
- Prior experience supporting life sciences research teams or building research infrastructure.
- Familiarity with omics and single-cell data, neural time series and neuroimaging.
- Computer vision experience, especially for microscopy, medical imaging, or scientific image analysis.
- Familiarity with n8n or similar workflow orchestration platforms.
- Experience deploying and managing production-scale LLMs (AWS SageMaker, Azure ML, Hugging Face).
- Practical fine-tuning skills (LoRA, full-model fine-tuning, hyperparameter optimization).
- Experience with containerization (Docker) and orchestration systems (Kubernetes).
- Solid understanding of MLOps and LLMOps tools and practices (MLFlow, Grafana, Prometheus).
Technical Stack
- Languages & Frameworks: Python, FastAPI, Transformers, PyTorch, TensorFlow, LangChain, LangGraph
- Data & Retrieval: FAISS, PGVector, Qdrant
- Infrastructure & Orchestration: Docker, Kubernetes, n8n
- ML Platforms & Tools: AWS SageMaker, Azure ML, Hugging Face, MLFlow, Grafana, Prometheus
Team & Environment
Collaborate closely with scientists, engineers, and operators across the company.
Benefits & Compensation
- Competitive compensation.
- Collaborative and supportive culture with mission-driven colleagues.
Work Mode
This is a hybrid role, primarily remote with trips to the labs.
E184 is an equal opportunity employer.
