IMO HealthRemote
Senior AI / MLOps Engineer – Clinical AI
United States
Full-time
1 week ago
$140,000 - $200,000 USD
H1B Sponsor Likely
Key skills
MLOps expertiseCloud platforms AWSCloud platforms AzureCI/CD pipelinesPythonJavaContainerization DockerContainerization KubernetesNLP conceptsMLOps tools MLflowMLOps tools SageMakerMLOps tools KubeflowProblem-solving skillsCommunication skillsCollaboration skillsSelf-starterAIArtificial IntelligenceMachine LearningMLNLPGenerative AILarge Language ModelsPyTorchTensorFlowHugging FaceMLOpsMLflowKubeflowAWSAzureKubernetesDockerSageMakerAgileCI/CDCommunicationCollaboration
About this role
IMO Health combines strengths in software development, artificial intelligence, and clinical expertise to create AI-driven solutions. They are seeking a Senior AI / MLOps Engineer to own the entire machine learning lifecycle, ensuring the operationalization of AI models and infrastructure for clinical data processing.
Responsibilities:
- Own the full ML lifecycle, including data ingestion, model training, validation, deployment, monitoring, retraining, and retirement
- Transition AI/ML models from prototypes into scalable, production-ready systems
- Build, deploy, and maintain CI/CD pipelines for ML 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 to improve efficiency, consistency, and reliability in retraining and deployment workflows
- Integrate large language models (LLMs), generative AI, and NLP solutions into IMO Health’s Clinical AI products, focusing on unstructured clinical data
- Develop scalable inference pipelines and APIs to deliver AI capabilities to customer-facing solutions
- Apply containerization (Docker, Kubernetes) and Infrastructure-as-Code to manage production environments
- Implement monitoring, alerting, and performance dashboards to ensure model quality, detect drift, and maintain operational SLAs
- Optimize deployed models for latency, throughput, reliability, and cost efficiency
- Participate in system design and architecture discussions, providing expertise in MLOps and AI deployment best practices
- Collaborate in an Agile environment with cross-functional teams, aligning technical solutions with product and business goals
Requirements:
- 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, maintaining, and scaling 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, monitoring, and observability for ML systems
- Working knowledge of NLP concepts (tokenization, embeddings, classification, sequence modeling); healthcare domain exposure is a plus
- Experience fine-tuning and deploying LLMs and generative AI solutions
- Strong problem-solving skills with the ability to design scalable, reliable, and maintainable ML systems
- Excellent communication and collaboration skills in cross-functional, distributed teams
- Self-starter with the ability to work independently and contribute from day one
- 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)