MLOps Engineer

Company Description

At MindWise, we are dedicated to revolutionizing the US healthcare industry through cutting-edge IT solutions. We provide tailored technology services that empower healthcare organizations to deliver better patient outcomes, enhance operational efficiency, and drive innovation. Our offerings include custom software development, healthcare IT consulting, and advanced healthcare analytics. Our team comprises experienced professionals who intimately understand the challenges and nuances of the US healthcare sector, and we believe in forging strong partnerships with our clients to deliver solutions that exceed expectations.

Role Description

This is a full-time remote role for an MLOps Engineer. The MLOps Engineer will be responsible for implementing and managing machine learning pipelines and infrastructure. Day-to-day tasks will include developing and maintaining scalable architecture for data processing and model deployment, collaborating with data scientists to optimize model performance, and ensuring the reliability and efficiency of machine learning solutions. The role also involves managing cloud-based resources and ensuring compliance with security and data protection standards.

Key Responsibilities

Cloud Infrastructure Management

o Design, deploy, and maintain AWS resources (EC2, ECS, Elastic Beanstalk, Lambda, VPC, VPN)

o Implement infrastructure-as-code using Terraform and Docker for consistent and reproducible deployments

o Optimize cost, performance, and security of compute and storage solutions

Database & Server Architecture

o Manage production-grade RDS MySQL instances with high availability, security, and backups

o Design scalable server-side infrastructure and ensure tight integration with Django-based services

Job Scheduling & Data Pipelines

o Build and monitor asynchronous task workflows with Celery, SQS, and SNS

o Manage data processing pipelines, ensuring timely and accurate job execution and messaging

Monitoring & Logging

o Set up and maintain CloudWatch dashboards, alarms, and centralized logging for proactive incident detection and resolution

Machine Learning & NLP Infrastructure

o Support deployment of NLP models on SageMaker and Bedrock, and manage interaction with vector databases and LLMs

o Assist in productionizing model endpoints, workflows, and monitoring pipelines

CI/CD & Automation

o Maintain and improve CI/CD pipelines using CircleCI

o Ensure automated testing, deployment, and rollback strategies are reliable and efficient

Healthcare Data Integration

o Support ingestion and transformation of clinical data using HL7 standards, Mirth Connect, and Java-based parsing tools

o Enforce data security and compliance best practices in handling PHI and other sensitive healthcare data

Qualifications

• 5+ years of experience in cloud infrastructure (preferably AWS)

• Strong command of Python/Django and container orchestration using Docker

• Proficiency with Terraform, infrastructure-as-code best practices

• Experience in setting up and managing messaging systems (Celery, SQS, SNS)

• Understanding of NLP or ML model operations in production environments

• Familiarity with LLM frameworks, vector databases, and SageMaker workflows

• Strong CI/CD skills (CircleCI preferred)

• Ability to work independently and collaboratively across engineering and data science teams

Nice to Have

• Exposure to HIPAA compliance, SOC2, or healthcare regulatory requirements

• Experience scaling systems in a startup or early-growth environment

• Contributions to open-source or community infrastructure projects

• Hands-on experience with HL7, Mirth Connect, and Java for healthcare interoperability is a big plus