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Strong software engineering skills: Python, APIs, microservices, database design, Git. We're hiring a Staff AI/ML Engineer & Technical Lead to own the architecture and delivery of scalable, enterprise-grade AI applications.

<p><strong>Job Title:</strong> Staff AI/ML Full-Stack Engineer & Technical Lead (Contract ? 1 Year)<br/><strong>Location:</strong> Remote (Normal, IL)<br/><strong>Employment Type:</strong> Full-Time</p><hr/><h3><strong>Overview</strong></h3><p>We're hiring a Staff AI/ML Engineer & Technical Lead to own the architecture and delivery of scalable, enterprise-grade AI applications. This is a hands-on leadership role spanning full-stack development, cloud infrastructure, and end-to-end ML system design.</p><hr/><h3><strong>Responsibilities</strong></h3><ul><li>Lead system architecture, technology selection, and integration design</li><li>Build and scale full-stack applications (React/Vue/Streamlit/Angular + Python/Golang/Rust)</li><li>Design and deploy cloud-native systems on AWS using Docker and Kubernetes</li><li>Develop REST and GraphQL APIs for internal and external use</li><li>Implement CI/CD pipelines, automated testing, and IaC (Terraform, Pulumi)</li><li>Optimize performance, scalability, and reliability across systems</li><li>Mentor engineers and enforce best practices through code/design reviews</li><li>Partner with product and business teams to deliver impactful solutions</li></ul><hr/><h3><strong>Requirements</strong></h3><ul><li>Strong experience in full-stack engineering and system architecture</li><li>Deep knowledge of AWS and Databricks (required); GCP is a plus</li><li>Expertise in database selection, deployment, and DevOps practices</li><li>Hands-on experience with ML and LLM systems (RAG, vector DBs, embeddings)</li><li>Solid understanding of MLOps, including deployment and monitoring pipelines</li><li>Experience building and deploying production-grade AI/ML applications end-to-end </li></ul><br/><br/><h3><strong>Required Qualifications</strong></h3><ul><li>Bachelor's degree in Computer Science (required)</li><li>10+ years of enterprise cloud deployment experience; 5+ years in software development</li><li>5+ years of hands-on experience with AWS and Databricks in MLOps environments</li><li>Strong background as a hands-on software lead building cloud infrastructure and platforms</li></ul><hr/><h3><strong>Core Expertise</strong></h3><ul><li>Architect and deploy end-to-end AI/ML systems, including traditional ML and RAG-based applications</li><li>Design agentic AI pipelines and reusable frameworks for team-wide contribution</li><li>Define best practices for model serving, data pipelines, and MLOps strategies</li><li>Hands-on experience with model development and system architecture</li></ul><hr/><h3><strong>Technical Skills</strong></h3><ul><li>Expertise in ML, deep learning, LLMs, embeddings, and RAG frameworks</li><li>Strong software engineering skills: Python, APIs, microservices, database design, Git</li><li>Experience with AWS, Databricks (required), and GCP (preferred)</li><li>Proficiency in containerization and orchestration (Docker, Kubernetes)</li><li>Solid understanding of MLOps, CI/CD for AI, and production monitoring</li><li>Experience with distributed systems, scalable architectures, and data pipelines</li><li>Database selection, deployment, and optimization with strong DevOps practices</li></ul><hr/><h3><strong>Preferred Qualifications</strong></h3><ul><li>Experience with event-driven architectures and messaging systems (Kafka, RabbitMQ, NATS)</li><li>Familiarity with authentication/authorization (OAuth2, JWT, SSO)</li><li>Knowledge of observability tools (Prometheus, Grafana, OpenTelemetry)</li><li>Experience building large-scale enterprise or SaaS platforms</li><li>Proficiency in Python, Golang, or Rust</li><li>Experience in manufacturing, predictive maintenance, or controls engineering</li></ul><hr/><h3><strong>Soft Skills</strong></h3><ul><li>Strong problem-solving and decision-making in complex technical environments</li><li>Ability to lead architectural direction and influence across teams</li><li>Clear communication with both technical and non-technical stakeholders</li></ul>

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Senior Software Cloud Fullstack Developer (Self Driving)

Amazon Web Services (AWS)

Apache Kafka

Application Programming Interface (API)

Architectural Services

Artificial Intelligence (AI)

Authentication

Best Practices

Cloud Computing

Code Reviews

Communication Skills

Computer Science

Continuous Deployment/Delivery

Continuous Integration

Control Engineering

Data Management

Data Modeling

Database Design

Deep Learning

DevOps

Distributed Computing

Docker

Engineering

GCP (Good Clinical Practices)

Go Programming Language (Golang)

GraphQL

Leadership

Manufacturing

Mentoring

Messaging Technology

Microservices

OAuth

Performance Tuning/Optimization

Problem Solving Skills

Production Control

Python Programming/Scripting Language

REST (Representational State Transfer)

RabbitMQ

React.js

Single Sign-On (SSO)

Software Development

Software Engineering

Software as a Service (SaaS)

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Test Automation

Vue.js

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