Senior AI Engineer

Intelligent Medical Objects (IMO)

full-time

Posted on: 9/17/2025

Origin: • 🇺🇸 United States • Illinois

✨ AI Apply

💰 $150,000 - $200,000 per year

Senior

AWSAzureCloudDockerJavaKubernetesPythonPyTorchTensorflow

About the role

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.

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.