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

Job Description

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 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 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 , 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 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 ():

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  • Hands-on experience with Retrieval-Augmented (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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