IMO Health is a clinical data intelligence company, improving how data is used across the healthcare landscape
The Role
The Staff AI Engineer will design, build, and maintain scalable AI systems, integrate NLP solutions, and mentor junior developers while collaborating with cross-functional teams.
Summary Generated by Built In
At IMO Health, we combine strengths in software development, artificial intelligence, and clinical expertise to create AI-driven solutions that enhance access to reliable health information, support clinical decision-making, and improve patient outcomes.
We are seeking a Staff AI Engineer to join our Software Engineering team, with strong background in designing, building, deploying, and maintaining AI solutions in production, with an emphasis on software engineering principles. This role is critical in bridging the gap between the theoretical capabilities of AI and its practical implementation by operationalizing AI models, building AI systems that are scalable, robust, and reliable in real-world environments.
The ideal candidate is a hands-on engineer with strong software engineering, data engineering, MLOps, DevOps, and cloud engineering expertise, capable of owning the full development lifecycle – from designing, architecting, and developing AI solutions to deployment, monitoring, and optimization. You will work closely with cross-functional partners who research and prototype models and integrate AI features into IMO Health products.
WHAT YOU’LL DO:
- Collaborate with cross-functional teams to transition AI/ML models from prototypes into scalable, production-ready systems.
- Lead system design and architecture discussions, bringing expertise in AI engineering, MLOps, and AI deployment best practices.
- Write high-quality source code, including detailed documentation and high-level technical designs in collaboration with other engineers.
- Develop and maintain AI-driven applications, ensuring high performance, scalability, reliability, and security, optimizing for latency, throughput, and cost.
- Integrate large language models (LLMs), generative AI, and NLP solutions into IMO Health’s products, with a focus on unstructured clinical data.
- Apply containerization (Docker, Kubernetes) and Infrastructure-as-Code to manage production environments.
- Collaborate in an Agile environment with cross-functional teams, aligning technical solutions with product and business goals.
- Implement creative solutions to technical challenges, applying out-of-the-box thinking to improve existing products.
- Conduct and lead root cause analysis on defects, ensuring fixes are implemented correctly.
- Guide Agile teams on best practices across all SDLC activities. Mentor junior developers.
- Champion technical standards and architectural alignment.
- Advocate for defining and testing Non-Functional Requirements (Availability, Scalability, Reliability, and Maintainability).
- Collaborate with team members while fostering trust, commitment, and accountability.
- Drive discovery and minimization of technical debt, proactively addressing implications and consequences of technical decisions.
WHAT YOU’LL NEED:
- 8+ years of professional experience in software engineering, AI/ML engineering, or related roles, building production-grade web applications.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field (or equivalent experience).
- Strong foundation in computer science fundamentals, including data structures, algorithms, design patterns, operating systems, and networking.
- Strong coding skills in Python or Java, with experience in software engineering best practices.
- Experience in developing AI-powered applications, including LLM integration, prompt engineering, and agentic concepts.
- Experience fine-tuning and deploying large language models (LLMs) and generative AI solutions in production.
- Solid hands-on experience with cloud platforms (AWS or Azure), containerization, and Infrastructure-as-Code.
- Experience with MLOps tools and workflows (e.g., MLflow, SageMaker, Kubeflow).
- Experience with CI/CD pipelines, automation, and monitoring.
- Working knowledge of NLP concepts (tokenization, embeddings, classification, sequence modeling) — healthcare domain exposure is a plus.
- Experience working with Elasticsearch and vector databases for embedding-based search and retrieval.
- Ability to translate business needs into optimal technical implementations while balancing technical debt and delivery speed.
- Strong problem-solving mindset to handle complex technical challenges and make informed architectural decisions.
- Experience in high-performance, scalable system design.
- Excellent collaboration skills, working effectively with cross-functional teams including Product, Architecture, and Data Science.
- Passion for AI technologies and innovation, particularly in applications for healthcare.
- Excellent communication and collaboration skills in cross-functional, distributed teams.
- Self-starter with the ability to work independently and contribute from day one.
NICE TO HAVE:
- Experience with clinical or healthcare AI applications.
- Familiarity with Hugging Face, PyTorch, TensorFlow, or other modern ML frameworks.
- AWS Associate-level certification (Machine Learning Engineer or Solutions Architect).
Top Skills
AWS
Azure
Docker
Elasticsearch
Java
Kubeflow
Kubernetes
Mlflow
Python
Sagemaker
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The Company
What We Do
We are a team of dedicated clinical terminologists, data scientists, industry subject matter experts, and informaticists who helped facilitate the evolution from analogue to digital capture of clinical events, the precise code-mapping that simplifies complex workflows, and the translation of unstructured into structured data. We “wrote the digital dictionary” used in every major EHR, and we are leveraging clinical AI to generate insights that expand and deepen our impact across the healthcare ecosystem.
At the end of the day, we don’t make decisions for our clients. We provide them with the digital tools to enable sound decision-making.
Why Work With Us
We are building a clinical intelligence stack—medical ontology, human expertise, and AI—that makes data more useful and more powerful. By enhancing data’s structure, richness, and precision, we reduce noise and error, streamline complexity, and create clarity across the clinical information chain.
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