Lead MLOps Engineer

Summary

Join Arine, a rapidly growing healthcare technology company, as a Lead MLOps/LLMOps Engineer. You will lead the design, deployment, and monitoring of reliable pipelines for AI-driven systems. Partner with engineers and data scientists to ensure models are production-ready, secure, and scalable. This hands-on role involves broad technical ownership across MLOps, LLMOps, and backend systems. You will mentor other engineers and build APIs and infrastructure. Help implement automated evaluation and auditing pipelines for AI model output. Collaborate cross-functionally to deliver ML/LLM capabilities into production environments. Arine offers a dynamic role with unparalleled learning and growth prospects, collaborating with experienced professionals in a growing start-up revolutionizing healthcare.

Requirements

• 10+ years of experience in backend engineering, MLOps, platform engineering, or related roles — ideally at a Staff-level or equivalent
• Proven track record of shipping production AI/ML and GenAI systems at scale
• Deep experience with AWS-native infrastructure and services (e.g., S3, Lambda, Bedrock, SageMaker, CloudWatch, ECS/Fargate)
• Proficient in Python and Pytorch , with strong software engineering fundamentals and comfort working with infrastructure-as-code tools (e.g., Terraform, GitHub Actions) to manage cloud-based deployment pipelines
• Demonstrated success setting up MLOps and LLMOps pipelines, including Deep Learning-based pipelines — from training and evaluation through deployment, monitoring, and retraining
• Knowledge of LLMOps best practices : prompt management, cost/performance optimization, failure handling, and agentic flow orchestration
• Experience setting up monitoring, alerting, and governance processes for AI models and GenAI features
• Strong cross-functional collaborator — able to partner with ML and GenAI engineers to quickly translate ideas into scalable systems
• Ability to pass a background check
• Must live in and be eligible to work in the United States

Responsibilities

• Lead MLOps and LLMOps: Define and implement robust practices for versioning, training, evaluation, deployment, and monitoring of both classical ML models and generative AI systems
• Agentic System Support: Help operationalize agent-based architectures and workflows, ensuring stability, observability, and integration with backend systems
• Mentor and Guide: Provide technical mentorship to other engineers on the team, helping them own the productionization of AI/ML pipelines
• Backend Engineering: Build and maintain APIs, Lambda functions, and infrastructure that power AI/ML systems, ensuring clean integration with Arine’s platform
• Model Evaluation and Governance: Help implement automated evaluation and auditing pipelines for ML/LLM output, ensuring systems are operating safety, reliability, and in a cost-effective manner
• Tooling and Automation: Set up CI/CD pipelines, experiment tracking, model registries, and evaluation sandboxes to accelerate AI delivery
• Cross-Functional Collaboration: Partner with AI engineers, data scientists, product teams, and DevOps to ensure ML/LLM capabilities are delivered smoothly into production environments

Preferred Qualifications

• Hands-on experience as a machine learning engineer or prompt engineer , with empathy for what it takes to build high-quality AI outputs
• Experience working in healthcare or other regulated environments with privacy and compliance constraints

Benefits

The salary range for this position is: $180,000-190,000/year