MLOps Engineer

Stefanini Group • Dearborn, MI

3d • Onsite

About The Position

Stefanini Group is hiring! Stefanini is looking for a MLOps Engineer (Dearborn, MI) For quick apply, please reach out to Navneet Pathak at 248-213-3677/[email protected] We are seeking an experienced AI Engineer to design, develop, and deploy intelligent solutions that leverage Machine Learning, Large Language Models (LLMs), and emerging Agentic AI capabilities to transform business processes and drive operational efficiency. The ideal candidate will have hands-on experience building and operationalizing AI/ML solutions in enterprise environments, with a strong focus on Generative AI, intelligent automation, and cloud-native architectures.

Requirements

• Python (advanced)
• SQL
• Machine Learning & Deep Learning
• LLMs, Prompt Engineering, RAG, Embeddings
• Agentic AI / AI Agents / Tool Calling
• Vector Databases
• ML Frameworks: Scikit-learn, TensorFlow, PyTorch
• MLOps: MLflow, Airflow, CI/CD, model deployment & monitoring
• Cloud: AWS or GCP
• Docker, Kubernetes
• API development (FastAPI / Flask)
• Data pipelines (ETL), data lakes/warehouses
• Strong system design & production AI experience
• 6+ years of experience in IT; 4+ years in development
• Experience designing and implementing Agentic AI solutions, multi-step workflows, autonomous agents, and tool-calling architectures.
• Proficient with AI orchestration frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, and similar technologies.
• Hands-on experience with MLOps tools including MLflow, Airflow, Vertex AI, SageMaker, and Kubeflow.
• Expertise in containerization and orchestration technologies such as Docker and Kubernetes.
• Familiarity with vector databases, embeddings, Retrieval-Augmented Generation (RAG), and semantic search architectures.
• Strong programming experience in Python, including backend development, API design, automation, and software engineering best practices.
• Experience building, deploying, and supporting machine learning models in production environments with frameworks like Scikit-learn, TensorFlow, and PyTorch.
• Practical experience developing applications using Large Language Models (LLMs), prompt engineering, and Generative AI technologies.
• Experience building AI solutions on cloud platforms such as GCP and AWS.
• Strong understanding of the software development lifecycle, version control, testing, and deployment practices.
• Experience working with enterprise-scale data environments, data lakes, and optimizing AI systems for scalability, performance, reliability, and cost efficiency.
• Experience building AI-powered products, dashboards, analytics solutions, or intelligent automation platforms.

Responsibilities

• Design, develop, and deploy machine learning models, including predictive, optimization, and Generative AI solutions.
• Build end-to-end AI workflows encompassing data ingestion, feature engineering, model training, deployment, monitoring, and continuous improvement.
• Develop and implement LLM-powered applications, including Retrieval-Augmented Generation (RAG), prompt orchestration, agentic workflows, and tool integrations.
• Create scalable APIs and AI services that seamlessly integrate with enterprise applications and business processes.
• Establish and maintain MLOps practices, including automated training, deployment, monitoring, retraining, and performance management.
• Ensure AI solutions are reliable, scalable, secure, and optimized for production environments.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior