
Making buildings smarter.
Ai/ML Engineer
薪酬
$85,000 - $107,000
必备技能
Python
Terraform
Azure ML
Azure DevOps
Docker
Kubernetes
Bash
PowerShell
MLOps
Johnson Controls International (JCI) is looking for a Machine Learning / Platform Engineer to join our growing AI and Data Platform team. This role is pivotal in enabling enterprise-scale ML and generative AI capabilities by building secure, scalable, and automated infrastructure on Azure using Terraform and Azure DevOps.
You’ll work at the intersection of ML, DevOps, and cloud engineering—building the foundation that supports real-time LLM inference, retraining, orchestration, and integration across JCI’s product and operations landscape.
How you will do itML Platform Engineering & MLOps (Azure-Focused)
-
Build and manage end-to-end ML/LLM pipelines on Azure ML using Azure DevOps for CI/CD, testing, and release automation.
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Operationalize LLMs and generative AI solutions (e.g., GPT, LLaMA, Claude) with a focus on automation, security, and scalability.
-
Develop and manage infrastructure as code using Terraform, including provisioning compute clusters (e.g., Azure Kubernetes Service, Azure Machine Learning compute), storage, and networking.
-
Implement robust model lifecycle management (versioning, monitoring, drift detection) with Azure-native MLOps components.
Infrastructure & Cloud Architecture
-
Design highly available and performant serving environments for LLM inference using **Azure Kubernetes Service (AKS)**and Azure Functions or App Services.
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Build and manage RAG pipelines using vector databases (e.g., Azure Cognitive Search, Redis, FAISS) and orchestrate with tools like Lang Chain or Semantic Kernel.
-
Ensure security, logging, role-based access control (RBAC), and audit trails are implemented consistently across environments.
Automation & CI/CD Pipelines
-
Build reusable Azure DevOps pipelines for deploying ML assets (data pre-processing, model training, evaluation, and inference services).
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Use Terraform to automate provisioning of Azure resources, ensuring consistent and compliant environments for data science and engineering teams.
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Integrate automated testing, linting, monitoring, and rollback mechanisms into the ML deployment pipeline.
Collaboration & Enablement
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Work closely with Data Scientists, Cloud Engineers, and Product Teams to deliver production-ready AI features.
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Contribute to solution architecture for real-time and batch AI use cases, including conversational AI, enterprise search, and summarization tools powered by LLMs.
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Provide technical guidance on cost optimization, scalability patterns, and high-availability ML deployments.
Qualifications & Skills Required Experience
-
Bachelor’s or Master’s in Computer Science, Engineering, or a related field.
-
5+ years of experience in ML engineering, MLOps, or platform engineering roles.
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Strong experience deploying machine learning models on Azure using Azure ML and Azure DevOps.
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Proven experience managing infrastructure as code with Terraform in production environments.
Technical Proficiency
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Proficiency in Python(Py Torch, Transformers, Lang Chain) and Terraform, with scripting experience in Bash or PowerShell.
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Experience with Docker and Kubernetes, especially within Azure (AKS).
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Familiarity with CI/CD principles, model registry, and ML artifact management using Azure ML and Azure DevOps Pipelines.
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Working knowledge of vector databases, caching strategies, and scalable inference architectures.
Soft Skills & Mindset
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Systems thinker who can design, implement, and improve robust, automated ML systems.
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Excellent communication and documentation skills—capable of bridging platform and data science teams.
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Strong problem-solving mindset with a focus on delivery, reliability, and business impact.
Preferred Qualifications
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Experience with LLMOps, prompt orchestration frameworks (Lang Chain, Semantic Kernel), and open-weight model deployment.
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Exposure to smart buildings, IoT, or edge-AI deployments.
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Understanding of governance, privacy, and compliance concerns in enterprise GenAI use cases.
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Certification in Azure (e.g., Azure Solutions Architect, Azure AI Engineer, Terraform Associate) is a plus.
HIRING SALARY RANGE: $85,000 - 107,000 (Salary to be determined by the education, experience, knowledge, skills, and abilities of the applicant, internal equity, location and alignment with market data.) This position includes a competitive benefits package. For details, please visit the About Us tab on the Johnson Controls Careers site at https://jobs.johnsoncontrols.com/about-us
Johnson Controls International plc. is an equal employment opportunity and affirmative action employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, protected veteran status, genetic information, sexual orientation, gender identity, status as a qualified individual with a disability or any other characteristic protected by law. To view more information about your equal opportunity and non-discrimination rights as a candidate, visit EEO is the Law. If you are an individual with a disability and you require an accommodation during the application process, please visit here.
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关于Johnson Controls

Johnson Controls
Series BJohnson Controls International plc is an American-Irish multinational conglomerate headquartered in Cork, Ireland, that produces fire, HVAC, and security equipment for buildings. As of mid-2019, it employed 105,000 people in around 2,000 locations across six continents.
10,001+
员工数
Cork
总部位置
评价
10条评价
4.0
10条评价
工作生活平衡
3.2
薪酬
3.8
企业文化
4.1
职业发展
3.4
管理层
3.1
72%
推荐率
优点
Good benefits and compensation
Supportive team culture and friendly coworkers
Flexible work arrangements and remote options
缺点
Heavy workload and high-pressure environment
Limited career advancement opportunities
Management responsiveness issues
薪资范围
195个数据点
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Data Scientist
0份报告
$120,000
年薪总额
基本工资
$120,000
股票
-
奖金
-
$102,000
$138,000
面试评价
2条评价
难度
2.5
/ 5
时长
14-28周
录用率
50%
体验
正面 50%
中性 50%
负面 0%
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Hiring Manager Interview
5
Offer
常见问题
Technical Knowledge
Behavioral/STAR
Past Experience
Problem Solving
Culture Fit
最新动态
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