Senior AI Engineer

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).