Stefanini North America and APAC

MLOps Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an MLOps Engineer in Dearborn, MI, with a contract length of "Unknown" and a pay rate of "Unknown." Key skills required include Python, Machine Learning, GCP, and experience with Generative AI and MLOps tools. A Bachelor's degree is required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
June 13, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Dearborn, MI
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🧠 - Skills detailed
#Docker #Data Pipeline #PyTorch #Flask #Version Control #Programming #Data Science #Consulting #ML (Machine Learning) #GCP (Google Cloud Platform) #Airflow #SQL (Structured Query Language) #AI (Artificial Intelligence) #Monitoring #"ETL (Extract #Transform #Load)" #Deep Learning #Databases #Automation #AWS (Amazon Web Services) #API (Application Programming Interface) #SageMaker #Kubernetes #Model Deployment #Cloud #MLflow #Langchain #Python #Data Ingestion #Scala #Data Lake #FastAPI #TensorFlow #Deployment
Role description
Details: Job Description 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/navneet.pathak@stefanini.com 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. 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. Job Requirements Details: Skills Required • Python, Machine Learning, Data Science, GCP, Big Query • 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 Experience Required • 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. Education Required • Bachelor's Degree Education Preferred • Master's degree • Listed salary ranges may vary based on experience, qualifications, and local market. Also, some positions may include bonuses or other incentives • • • Stefanini takes pride in hiring top talent and developing relationships with our future employees. Our talent acquisition teams will never make an offer of employment without having a phone conversation with you. Those face-to-face conversations will involve a description of the job for which you have applied. We will also speak with you about the process, including interviews and job offers. About Stefanini Group The Stefanini Group is a global provider of offshore, onshore and near shore outsourcing, IT digital consulting, systems integration, application, and strategic staffing services to Fortune 1000 enterprises around the world. Our presence is in countries like the Americas, Europe, Africa, and Asia, and more than four hundred clients across a broad spectrum of markets, including financial services, manufacturing, telecommunications, chemical services, technology, public sector, and utilities. Stefanini is a CMM level 5, IT consulting company with a global presence. We are a CMM Level 5 company.