MLOps Engineer; Remote in RI

Job Description An innovative organization delivering cutting-edge AI, machine learning, and cloud data solutions is looking for a Staff MLOps Engineer to join its fully remote team. This opportunity is specifically targeting professionals located in Rhode Island who thrive on building scalable machine learning infrastructure and enabling production-ready AI systems.
This role is designed for an experienced engineer who enjoys solving complex technical challenges at the intersection of cloud platforms, machine learning operations, distributed systems, and generative AI. You will help establish the foundation that supports model deployment, monitoring, governance, and lifecycle management for enterprise-scale AI applications.
As a senior technical contributor, you will partner closely with software engineers, data scientists, AI specialists, and cloud teams to develop robust solutions that enable reliable, secure, and efficient machine learning workloads in production.

• 10+ years of professional experience in software engineering, platform engineering, or cloud infrastructure
• Strong experience designing and operating distributed systems in production environments
• Proven track record leading complex technical initiatives and driving engineering best practices
• Significant experience building and supporting MLOps platforms for production workloads
• Hands-on experience deploying, monitoring, and maintaining large language model (LLM) applications
• Deep understanding of machine learning lifecycle management, model deployment, and governance
• Experience implementing Retrieval-Augmented Generation (RAG) solutions and vector-based retrieval systems
• Advanced proficiency with Python and Type Script
• Strong experience developing APIs and backend services
• Expertise with AWS services and cloud-native architectures
• Experience with Docker and containerized application deployment
• Familiarity with Infrastructure as Code technologies such as AWS CDK or Cloud Formation
• Strong knowledge of observability practices, monitoring solutions, and distributed tracing
• Experience securing multi-tenant environments and protecting regulated or sensitive data
• Ability to collaborate across teams and influence technical decisions

• Experience supporting agent-based AI workflows in production
• Familiarity with modern LLM orchestration frameworks and tooling
• Knowledge of AI infrastructure optimization, inference performance, and resource utilization
• Experience designing model evaluation frameworks and testing pipelines
• Exposure to multimodal AI systems involving image or scientific datasets
• Understanding of model tuning, distillation, and inference optimization techniques
• Experience working within regulated industries and compliance-driven environments
• Background supporting scientific, life sciences, pharmaceutical, or healthcare technology platforms
• Experience measuring and managing AI platform costs at scale

• Build and enhance the organization’s machine learning operations platform
• Develop scalable infrastructure supporting AI and machine learning applications
• Manage model deployment workflows, versioning processes, and release strategies
• Design solutions for both real-time inference and large-scale batch processing
• Implement secure architectures that support customer data isolation and governance requirements
• Create monitoring, logging, and alerting capabilities for production AI systems
• Establish validation and evaluation processes that improve AI reliability and quality
• Drive platform scalability, availability, performance, and operational efficiency
• Collaborate with engineering and data teams to support AI product development
• Contribute to CI/CD automation…