Cloud Software Engineer (Contract – Hybrid – Dearborn, MI)

Cloud Software Engineer (Contract – Hybrid – Dearborn, MI)

Our client, a global leader in defining the future of mobility, is actively seeking a highly skilled Cloud Software Engineer to join their Global Data Insight & Analytics (GDIA) organization. This contract position, based hybrid in Dearborn, Michigan (currently 2 days in-person at the office, subject to change), offers a unique opportunity to lead and advance their internal Data Science and AI/ML platform strategy.

You’ll be part of a dynamic, cross-functional team, collaborating closely and consistently with other engineers, business partners, product managers, and designers. This role involves frequent and iterative releases, with a primary focus on software engineering for machine learning and generative AI applications, as well as creating reusable AI/ML components. Join them and help define tomorrow’s transportation, leveraging cutting-edge technologies to accelerate your career potential and drive human progress.

What’s the Job? Engineering AI/ML Platforms for Future Mobility

As a Cloud Software Engineer, you will be a pivotal contributor to advancing the organization’s data science and AI/ML capabilities. Your role will blend hands-on development with strategic collaboration, focusing on building and optimizing platforms that leverage machine learning and generative AI for complex data insights.

• Deliver MLOps Platform and Gen AI Solutions in GCP: You will work closely with the Tech Anchor, Product Manager, and Product Owner to meticulously deliver MLOps (Machine Learning Operations) platforms and Generative AI (Gen AI) solutions in Google Cloud Platform (GCP). This involves leveraging Python and other tools to build robust, scalable platforms for data scientists and business users across the company. Your work will enable the full lifecycle of AI models, from experimentation to deployment and monitoring.
• Tackle Challenging AIOps and Gen AI Problems: You will collaborate with software engineers, ML engineers, and data scientists to tackle challenging AIOps (Artificial Intelligence for IT Operations) and Generative AI problems. This means designing and implementing solutions that use AI to automate IT operations, predict issues, and optimize performance. For Gen AI, you’ll work on applications that leverage Large Language Models (LLMs) and other generative models to create new content, synthesize information, or build intelligent agents.
• Maintain and Manage Current CI/CD Ecosystem and Tools: You will play a crucial role in maintaining and managing the current CI/CD (Continuous Integration/Continuous Delivery) ecosystem and tools. This ensures that the software delivery pipeline for AI/ML solutions is robust, efficient, and reliable. Your efforts will guarantee that code changes are integrated, tested, and deployed seamlessly and continuously.
• Automate and Continually Improve CI/CD and Release Processes: You will proactively find ways to automate and continually improve current CI/CD processes and release processes. This involves identifying manual bottlenecks, scripting repetitive tasks, and implementing innovative solutions to streamline the entire software delivery lifecycle. Your focus on automation will enhance efficiency, reduce errors, and accelerate the pace of innovation.
• Examine, Inspect Code/Scripts, and Resolve Issues: You will meticulously examine and inspect code/scripts related to the AI/ML platforms. This involves conducting thorough code reviews, analyzing system logs, and utilizing debugging tools to identify vulnerabilities, performance bottlenecks, or functional defects. Your keen eye for detail will be critical in effectively resolving issues and ensuring the high quality and reliability of the software.
• Innovate and Standardize Machine Learning Development Practices: You will actively help innovate and standardize machine learning development practices across the organization. This involves collaborating with data scientists and engineers to define best practices for model development, versioning, testing, and deployment. Your contributions will foster consistency, improve reproducibility, and enhance the overall efficiency of ML development workflows.
• Experiment, Innovate, and Share Knowledge: You will be encouraged to experiment, innovate, and actively share knowledge with the team. This fosters a culture of continuous learning and improvement, where new ideas are welcomed, tested, and disseminated, driving collective growth and technological advancement within the GDIA organization.
• Lead by Example in Paired Programming: You will lead by example in the use of Paired Programming for cross-training/upskilling, collaborative problem-solving, and accelerating speed to delivery. This practice emphasizes real-time collaboration, knowledge transfer, and immediate feedback, significantly enhancing code quality and team cohesion.
• Leverage Latest ML/Gen AI / GCP/AIOps/Kubernetes Technologies: You will continuously leverage the latest Machine Learning (ML), Generative AI (Gen AI), Google Cloud Platform (GCP), AIOps, and Kubernetes technologies. This ensures that the platforms and solutions you build remain at the cutting edge, providing the most advanced capabilities for data science and AI/ML initiatives.

What You’ll Bring: Essential Skills for a Cloud AI/ML Engineer

To excel in this role, you’ll need a strong academic background, extensive backend software engineering experience, and hands-on expertise with cloud platforms, machine learning operations, and generative AI.

Required Qualifications:

• Education: A Bachelor’s degree in Computer Science / Computer Engineering or a similar technical discipline is required. This academic foundation provides the essential theoretical knowledge for software engineering and advanced computing concepts.
• Backend Python Software Engineering Experience: You must possess 3+ years of verifiable work experience as a backend software engineer in Python, demonstrating exceptional software engineering knowledge. This indicates deep proficiency in building robust, scalable, and high-performance backend systems using Python.
• Cloud Engineering / Services Experience: You must have 2+ years of experience with Cloud Engineering / Services. This includes hands-on experience with major cloud platforms (preferably GCP, but AWS/Azure experience would be valuable), managing cloud resources, and understanding cloud-native development principles.
• Experience in MLOps and Gen AI (LLM & Applications): You must have direct experience in MLOps (Machine Learning Operations), demonstrating your ability to operationalize ML models. Crucially, you need Generative AI experience, including working with LLMs (Large Language Models) and development experience with building RAG (Retrieval-Augmented Generation) and Multi-Agent Applications. This highlights your ability to design and build sophisticated AI solutions.
• ML Workflow Orchestration Tools: You must have experience with ML workflow orchestration tools such as Airflow, Kubeflow, or similar platforms. This indicates your ability to design, schedule, and manage complex machine learning pipelines.
• Advanced Object-Oriented/Functional Programming: You possess advanced working knowledge of object-oriented/object functional programming languages, specifically Python, C/C++. This demonstrates versatility and depth in programming paradigms suitable for high-performance computing.
• DevOps Experience: You have hands-on experience in DevOps practices and tools, including CI/CD platforms like Jenkins/Tekton, for automating software delivery and infrastructure management.
• GCP Cloud Services Experience (Preferred): Experience with cloud services, preferably GCP Services like Vertex AI (for ML development and deployment), Cloud Functions (for serverless execution), and BigQuery (for data warehousing and analytics).
• Container Management Solution Experience: You have hands-on experience in container management solutions, specifically Kubernetes (for container orchestration) and Docker (for containerization).
• Scripting Language Experience: You are proficient in scripting languages such as Bash, PowerShell, or others, for automating system administration tasks and workflow orchestration.
• Infrastructure as Code (IaC) Experience: You have practical experience with Infrastructure as Code (IaC) tools such as Terraform, for provisioning and managing cloud infrastructure in a declarative and automated manner.

Preferred Qualifications:

• Master’s Degree in ML/CS: A Master’s degree focused in Computer Science / Machine Learning or a related field is highly preferred, indicating advanced academic specialization.
• GCP Deep Dive (GKE, Terraform, Infrastructure): More in-depth experience working with Google Cloud Platform (GCP), specifically Google Kubernetes Engine (GKE) for managing containerized applications, advanced use of Terraform for IaC, and broad knowledge of GCP infrastructure services.
• Programming Concepts: Experience with advanced programming concepts such as Paired Programming, Test Driven Development (TDD), etc., indicating a commitment to high-quality code and collaborative practices.
• Coding and Software Craftsmanship Practices: Knowledge of best practices in coding and software craftsmanship, emphasizing maintainability, readability, and robustness.
• Quick Learner and Open to New Technology: You are a quick learner and open to learning new technology, demonstrating adaptability and a proactive approach to skill development in a rapidly evolving field.
• Agile Practices Application: Experience applying agile practices to solution delivery, beyond just participating in ceremonies.
• Team-Oriented with Excellent Communication: You are team-oriented with excellent oral and written communication skills.
• Self-Starter with Innovative Solutions: You are a self-starter with the ability to identify existing bottlenecks and proactively come up with innovative solutions to drive continuous improvement.

If this Cloud Software Engineer role in Dearborn, MI, aligns with your expertise in Python backend development, your experience with GCP, MLOps, and Generative AI, and your passion for shaping the future of mobility, we encourage you to learn more about this exciting hybrid contract opportunity. This is a fantastic chance to lead and advance internal Data Science and AI/ML platform strategies within a global leader.

Are you ready to accelerate your career potential and help define tomorrow’s transportation through cutting-edge AI/ML?