Senior AI/ML Engineer - Generative AI & Intelligent Systems (Smart Buildings)

Job Title: Senior AI/ML Engineer – Generative AI & Intelligent Systems (Smart Buildings)

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Location: Glendale, WI 53209 (Hybrid)

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Contract Duration: 6 Months Contract with possibility of Extension

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Shift Structure: First Shift | Standard Daytime Business Hours, Monday through Friday

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Pay Rate: $60 - $65/hr on W2

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Portfolio Requirement: N/A (Technical code/system architecture discussion during interview)

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Visa Sponsorship: Standard onshore onboarding requirements apply.

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Job Description: Our client is an industry leader in smart facilities and Building Automation Systems (BAS), is seeking a Senior AI/ML Engineer to join their Controls Software Engineering team in Glendale, WI. In this dual-pillar technical leadership role, you will evolve mission-critical building platforms (serving data centers, hospitals, and pharmaceutical facilities) into AI-native architectures. You will architect, develop, and deploy production-grade Generative AI, Large Language Models (LLMs), and machine learning models across cloud and edge environments, while establishing enterprise-wide AI engineering standards, developer tooling, and MLOps practices.

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Key Responsibilities:

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• Pillar 1: Production AI/ML Product Engineering:
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• Design, build, and deploy production-ready AI/ML and Generative AI capabilities across cloud, edge, and on-premises environments.
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• Build end-to-end LLM-powered features, including operator copilots, intelligent alarm diagnostics, natural language interfaces, and autonomous recommendation systems.
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• Architect low-latency, scalable inference pipelines and integrate AI modules into existing Building Automation Systems (BAS) and IoT products.
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• Monitor, benchmark, and optimize model drift, accuracy, and reliability in mission-critical environments.
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• Pillar 2: Developer Acceleration & AI Governance:
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• Implement AI-assisted developer tooling (code generation, automated test synthesis, automated code review) to elevate team velocity.
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• Define and champion AI engineering standards, MLOps frameworks, model governance, and responsible AI guardrails across cross-functional engineering pods.
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• Mentor software engineers and data scientists on emerging LLM frameworks, model serving, and distributed systems architecture.
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Required Qualifications & Skills:

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• Software & ML Foundation: 7+ years of progressive software engineering experience combined with 5+ years of hands-on experience building and deploying machine learning models to production.
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• Core Tech Stack: Expert-level proficiency in Python and common AI/ML frameworks (PyTorch, TensorFlow, Scikit-learn).
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• Generative AI & LLMs: Proven track record building and integrating Generative AI and Large Language Model (LLM) solutions into live software products.
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• Cloud & Production Architecture: Strong understanding of scalable microservices, REST APIs, streaming data pipelines, and deployment on AWS, Azure, or GCP.
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• Education: Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related technical discipline.
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Stand-Out Skills (Preferred):

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• Hands-on experience with Retrieval-Augmented Generation (RAG) architectures, vector databases (e.g., Pinecone, Milvus, Chroma, pgvector), and prompt orchestration (LangChain, LlamaIndex).
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• Experience deploying containerized ML models to edge or IoT runtime environments (e.g., ONNX, TensorRT, Docker/Kubernetes).
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• Practical familiarity with industrial control systems, Building Automation Systems (BAS), BACnet, or commercial IoT telemetry.
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• Strong background in MLOps pipelines (MLflow, Kubeflow, CI/CD automated model evaluation).
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Actual Skills Required:

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1. Production Machine Learning & Generative AI (LLM) Engineering
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2. Python Mastery & Deep Learning Frameworks (PyTorch / TensorFlow)
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3. RAG Architecture, Vector Databases & Prompt Engineering
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4. Cloud & Edge Inference Deployment (AWS / Azure / GCP)
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5. AI Governance, MLOps & Developer Velocity Acceleration
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Recruiter Email ID: jevin@cube-hub.com

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