Overview
Remote
On Site
170k - 200k
Full Time
Skills
DevOps
Workflow
Amazon Web Services
Python
TypeScript
Databricks
Docker
Continuous Integration
Continuous Delivery
Communication
Vector Databases
Performance Tuning
Cloud Computing
Machine Learning Operations (ML Ops)
Artificial Intelligence
Machine Learning (ML)
Collaboration
Job Details
This role is for a Senior AI Platform Engineer working with a leading scientific data and AI organization. You'll build and scale cloud-native AI/ML infrastructure using AWS, Databricks, and modern MLOps tooling.
This opportunity is ideal for someone who wants to drive impactful AI platform development while working in a highly collaborative, growth-focused environment. You'll help enable production-grade AI workflows and shape next-gen data and model pipelines.
Required Skills & Experience
7+ years in software/infrastructure engineering
Strong AWS and IaC experience (CloudFormation, CDK)
Expert Python and TypeScript
Databricks MLflow production experience
Docker, CI/CD, and scalable ML infrastructure
Strong communication and cross-team collaboration
Desired Skills & Experience
Experience with LLM frameworks (e.g., DSPy)
RAG architectures and vector databases
LLM cost/performance optimization
Cloud-native observability tools
What You Will Be Doing Tech Breakdown
60% Cloud & MLOps
40% AI/ML Platform Engineering
Daily Responsibilities
70% Hands-On Engineering
10% Architecture & Planning
20% Team Collaboration
This opportunity is ideal for someone who wants to drive impactful AI platform development while working in a highly collaborative, growth-focused environment. You'll help enable production-grade AI workflows and shape next-gen data and model pipelines.
Required Skills & Experience
7+ years in software/infrastructure engineering
Strong AWS and IaC experience (CloudFormation, CDK)
Expert Python and TypeScript
Databricks MLflow production experience
Docker, CI/CD, and scalable ML infrastructure
Strong communication and cross-team collaboration
Desired Skills & Experience
Experience with LLM frameworks (e.g., DSPy)
RAG architectures and vector databases
LLM cost/performance optimization
Cloud-native observability tools
What You Will Be Doing Tech Breakdown
60% Cloud & MLOps
40% AI/ML Platform Engineering
Daily Responsibilities
70% Hands-On Engineering
10% Architecture & Planning
20% Team Collaboration
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.