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       Senior Software Cloud Fullstack Developer (Self Driving)

  •    Normal, IL

Job ID#: 3829

Category: Manufacturing

Position Type

Contractor (W-2)

Job Description

Job Title: Staff AI/ML Full-Stack Engineer & Technical Lead (Contract ? 1 Year)
Location: Remote (Normal, IL)
Employment Type: Full-Time

Overview

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.

Responsibilities

  • Lead system architecture, technology selection, and integration design
  • Build and scale full-stack applications (React/Vue/Streamlit/Angular + Python/Golang/Rust)
  • Design and deploy cloud-native systems on AWS using Docker and Kubernetes
  • Develop REST and GraphQL APIs for internal and external use
  • Implement CI/CD pipelines, automated testing, and IaC (Terraform, Pulumi)
  • Optimize performance, scalability, and reliability across systems
  • Mentor engineers and enforce best practices through code/design reviews
  • Partner with product and business teams to deliver impactful solutions

Requirements

  • Strong experience in full-stack engineering and system architecture
  • Deep knowledge of AWS and Databricks (required); GCP is a plus
  • Expertise in database selection, deployment, and DevOps practices
  • Hands-on experience with ML and LLM systems (RAG, vector DBs, embeddings)
  • Solid understanding of MLOps, including deployment and monitoring pipelines
  • Experience building and deploying production-grade AI/ML applications end-to-end 

Job Requirements

Required Qualifications

  • Bachelor's degree in Computer Science (required)
  • 10+ years of enterprise cloud deployment experience; 5+ years in software development
  • 5+ years of hands-on experience with AWS and Databricks in MLOps environments
  • Strong background as a hands-on software lead building cloud infrastructure and platforms

Core Expertise

  • Architect and deploy end-to-end AI/ML systems, including traditional ML and RAG-based applications
  • Design agentic AI pipelines and reusable frameworks for team-wide contribution
  • Define best practices for model serving, data pipelines, and MLOps strategies
  • Hands-on experience with model development and system architecture

Technical Skills

  • Expertise in ML, deep learning, LLMs, embeddings, and RAG frameworks
  • Strong software engineering skills: Python, APIs, microservices, database design, Git
  • Experience with AWS, Databricks (required), and GCP (preferred)
  • Proficiency in containerization and orchestration (Docker, Kubernetes)
  • Solid understanding of MLOps, CI/CD for AI, and production monitoring
  • Experience with distributed systems, scalable architectures, and data pipelines
  • Database selection, deployment, and optimization with strong DevOps practices

Preferred Qualifications

  • Experience with event-driven architectures and messaging systems (Kafka, RabbitMQ, NATS)
  • Familiarity with authentication/authorization (OAuth2, JWT, SSO)
  • Knowledge of observability tools (Prometheus, Grafana, OpenTelemetry)
  • Experience building large-scale enterprise or SaaS platforms
  • Proficiency in Python, Golang, or Rust
  • Experience in manufacturing, predictive maintenance, or controls engineering

Soft Skills

  • Strong problem-solving and decision-making in complex technical environments
  • Ability to lead architectural direction and influence across teams
  • Clear communication with both technical and non-technical stakeholders

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