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 Senior AI Engineer to join our Clinical AI team, supporting the deployment and maintenance of machine learning models in production. This role is critical to bridging the gap between research and product by operationalizing AI models, ensuring they scale reliably, and building the infrastructure that enables innovation in clinical data processing.
The ideal candidate is a hands-on engineer with strong MLOpsexpertise, capable of owning the full lifecycle of machine learning models – from training and fine-tuning through deployment, monitoring, and optimization. You will work closely with cross-functional partners who prototype models and integrate AI features into IMO products.
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 Senior AI Engineer to join our Clinical AI team, supporting the deployment and maintenance of machine learning models in production. This role is critical to bridging the gap between research and product by operationalizing AI models, ensuring they scale reliably, and building the infrastructure that enables innovation in clinical data processing. The ideal candidate is a hands-on engineer with strong MLOpsexpertise, capable of owning the full lifecycle of machine learning models – from training and fine-tuning through deployment, monitoring, and optimization. You will work closely with cross-functional partners who prototype models and integrate AI features into IMO products.
Compensation at IMO Health is determined by job level, role requirements, and each candidate’s experience, skills, and location. The listed base pay represents the target for new hires with individual compensation varying accordingly. These figures exclude potential bonuses, equity, or sales incentives, which may also be part of the total compensation package. Our recruiter will provide additional details during the hiring process. IMO Health also offers a comprehensive benefits package. To learn more, please visit IMO Health’s Careers Page.
WHAT YOU’LL DO:
Collaborate with cross-functional teams to transition AI/ML models from prototypes into scalable, production-ready systems.
Build, deploy, and maintain CI/CD pipelines for machine learning models, ensuring reproducibility, scalability, and reliability.
Design and implement cloud-based infrastructure (AWS, Azure, or equivalent) for training, inference, and monitoring of AI models.
Automate repetitive ML lifecycle tasks, improving efficiency and consistency in retraining and deployment workflows.
Integrate large language models (LLMs), generative AI, and NLP solutions into IMO Health’s Clinical AI products, with a focus on unstructured clinical data.
Develop scalable inference pipelines and APIs to deliver AI capabilities into customer-facing solutions.
Apply containerization (Docker, Kubernetes) and Infrastructure-as-Code to manage production environments.
Participate in system design and architecture discussions, bringing expertise in MLOps and AI deployment best practices.
Ensure performance, reliability, and security of deployed models, optimizing for latency, throughput, and cost.
Collaborate in an Agile environment with cross-functional teams, aligning technical solutions with product and business goals.
WHAT YOU’LL NEED:
5+ years of professional experience in software engineering, AI/ML engineering, or related roles.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field (or equivalent experience).
Strong coding skills in Python or Java, with experience in software engineering best practices.
Hands-on experience deploying and maintaining ML models in production environments.
Proficiency with cloud platforms (AWS or Azure), containerization, and Infrastructure-as-Code.
Experience with MLOps tools and workflows (e.g., MLflow, SageMaker, Kubeflow).
Familiarity with CI/CD pipelines, automation, and monitoring for machine learning systems.
Working knowledge of NLP concepts (tokenization, embeddings, classification, sequence modeling) — healthcare domain exposure is a plus.
Experience fine-tuning and deploying large language models (LLMs) and generative AI solutions.
Strong problem-solving skills with the ability to design scalable, reliable systems.
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.
Prior exposure to agentic AI and generative AI applications.
AWS Associate-level certification (Machine Learning Engineer or Solutions Architect).
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