Ai/ML Engineer
$85K - $107K/yr
This role is pivotal in enabling enterprise-scale ML and generative AI capabilities by building ... Design highly available and performant serving environments for LLM inference using Azure ...
$85K - $107K/yr
This role is pivotal in enabling enterprise-scale ML and generative AI capabilities by building ... Design highly available and performant serving environments for LLM inference using Azure ...
$85K - $107K/yr
This role is pivotal in enabling enterprise-scale ML and generative AI capabilities by building ... Design highly available and performant serving environments for LLM inference using Azure ...
San Antonio, TX · On-site
... inference, and monitoring in production environments. • Participate in continuous improvement of the ML infrastructure and processes for scalability and performance. Qualifications : Required : • ...
San Antonio, TX · On-site
... inference, and monitoring in production environments. • Participate in continuous improvement of the ML infrastructure and processes for scalability and performance. Qualifications : Required : • ...
Dallas, TX · On-site
... inference, and monitoring in production environments. • Participate in continuous improvement of the ML infrastructure and processes for scalability and performance. Qualifications : Required : • ...
Dallas, TX · On-site
... inference, and monitoring in production environments. • Participate in continuous improvement of the ML infrastructure and processes for scalability and performance. Qualifications : Required : • ...
Fort Worth, TX · On-site
... inference, and monitoring in production environments. • Participate in continuous improvement of the ML infrastructure and processes for scalability and performance. Qualifications : Required : • ...
Fort Worth, TX · On-site
... inference, and monitoring in production environments. • Participate in continuous improvement of the ML infrastructure and processes for scalability and performance. Qualifications : Required : • ...
Austin, TX · On-site
... inference, and monitoring in production environments. • Participate in continuous improvement of the ML infrastructure and processes for scalability and performance. Qualifications : Required : • ...
Austin, TX · On-site
... inference, and monitoring in production environments. • Participate in continuous improvement of the ML infrastructure and processes for scalability and performance. Qualifications : Required : • ...
Houston, TX · On-site
... inference, and monitoring in production environments. • Participate in continuous improvement of the ML infrastructure and processes for scalability and performance. Qualifications : Required : • ...
Houston, TX · On-site
... inference, and monitoring in production environments. • Participate in continuous improvement of the ML infrastructure and processes for scalability and performance. Qualifications : Required : • ...
Dallas, TX · On-site
$85K - $107K/yr
This role is pivotal in enabling enterprise-scale ML and generative AI capabilities by building ... Design highly available and performant serving environments for LLM inference using Azure ...
Dallas, TX · On-site
$85K - $107K/yr
This role is pivotal in enabling enterprise-scale ML and generative AI capabilities by building ... Design highly available and performant serving environments for LLM inference using Azure ...
Dallas, TX · On-site
$85K - $107K/yr
This role is pivotal in enabling enterprise-scale ML and generative AI capabilities by building ... Design highly available and performant serving environments for LLM inference using Azure ...
Dallas, TX · On-site
$85K - $107K/yr
This role is pivotal in enabling enterprise-scale ML and generative AI capabilities by building ... Design highly available and performant serving environments for LLM inference using Azure ...
Austin, TX · On-site
... inference, and monitoring in production environments. • Participate in continuous improvement of the ML infrastructure and processes for scalability and performance. Qualifications : Required : • ...
Austin, TX · On-site
... inference, and monitoring in production environments. • Participate in continuous improvement of the ML infrastructure and processes for scalability and performance. Qualifications : Required : • ...
Plano, TX · On-site
Core Responsibilities (AI/ML, Python, AWS, GenAI) * Design and implement end-to-end AI/ML and ... Build robust MLOps workflows, including model versioning, containerized training/inference ...
Quick apply
Plano, TX · On-site
Core Responsibilities (AI/ML, Python, AWS, GenAI) * Design and implement end-to-end AI/ML and ... Build robust MLOps workflows, including model versioning, containerized training/inference ...
Austin, TX · On-site
$120K - $225K/yr
Enable early firmware, driver, runtime, and ML stack bring-up on emulated hardware * Support execution of AI inference workloads (e.g., CNNs, transformers) on emulated Mythic accelerators
Austin, TX · On-site
$120K - $225K/yr
Enable early firmware, driver, runtime, and ML stack bring-up on emulated hardware * Support execution of AI inference workloads (e.g., CNNs, transformers) on emulated Mythic accelerators
$150K - $225K/yr
We build and operate ML, GenAI, Inference and Data Platforms and Services to provide a comprehensive suite of capabilities-serving business-critical needs across Apple's enterprise. We work on ...
$150K - $225K/yr
We build and operate ML, GenAI, Inference and Data Platforms and Services to provide a comprehensive suite of capabilities-serving business-critical needs across Apple's enterprise. We work on ...
$150K - $225K/yr
We build and operate ML, GenAI, Inference and Data Platforms and Services to provide a comprehensive suite of capabilities-serving business-critical needs across Apple's enterprise. We work on ...
$150K - $225K/yr
We build and operate ML, GenAI, Inference and Data Platforms and Services to provide a comprehensive suite of capabilities-serving business-critical needs across Apple's enterprise. We work on ...
Austin, TX · On-site
$120K - $225K/yr
Enable early firmware, driver, runtime, and ML stack bring-up on emulated hardware * Support execution of AI inference workloads (e.g., CNNs, transformers) on emulated Mythic accelerators
Quick apply
Austin, TX · On-site
$120K - $225K/yr
Enable early firmware, driver, runtime, and ML stack bring-up on emulated hardware * Support execution of AI inference workloads (e.g., CNNs, transformers) on emulated Mythic accelerators
We're looking for a strong technical leader with deep experience in ML serving, high-performance ... Lead the design and development of a SOTA Inference platform * Oversee the development of ...
We're looking for a strong technical leader with deep experience in ML serving, high-performance ... Lead the design and development of a SOTA Inference platform * Oversee the development of ...
We're looking for a strong technical leader with deep experience in ML serving, high-performance ... Lead the design and development of a SOTA Inference platform * Oversee the development of ...
We're looking for a strong technical leader with deep experience in ML serving, high-performance ... Lead the design and development of a SOTA Inference platform * Oversee the development of ...
Austin, TX · On-site
$120K - $225K/yr
Enable early firmware, driver, runtime, and ML stack bring-up on emulated hardware * Support execution of AI inference workloads (e.g., CNNs, transformers) on emulated Mythic accelerators
Austin, TX · On-site
$120K - $225K/yr
Enable early firmware, driver, runtime, and ML stack bring-up on emulated hardware * Support execution of AI inference workloads (e.g., CNNs, transformers) on emulated Mythic accelerators
Austin, TX · On-site
$120 - $180/hr
We build and operate ML, GenAI, Inference and Data Platforms and Services to provide a comprehensive suite of capabilities--serving business-critical needs across Apple's enterprise. We work on ...
Austin, TX · On-site
$120 - $180/hr
We build and operate ML, GenAI, Inference and Data Platforms and Services to provide a comprehensive suite of capabilities--serving business-critical needs across Apple's enterprise. We work on ...
Irving, TX · On-site
Preferred : • Financial domain expertise (risk, fraud, forecasting, customer intelligence). • Advanced ML topics: time series, graph ML, optimization, causal inference. • ONNX/TensorRT model ...
Irving, TX · On-site
Preferred : • Financial domain expertise (risk, fraud, forecasting, customer intelligence). • Advanced ML topics: time series, graph ML, optimization, causal inference. • ONNX/TensorRT model ...
Irving, TX · On-site
Development and Implement data pipelines and ML pipelines to facilitate model inference (both Real-time and batch) * Analyze large, complex data sets to identify the most performant way to process ...
Irving, TX · On-site
Development and Implement data pipelines and ML pipelines to facilitate model inference (both Real-time and batch) * Analyze large, complex data sets to identify the most performant way to process ...
| Aspect | ML Inference | Data Scientist |
|---|---|---|
| Required Credentials | Knowledge of machine learning models, programming skills | Degree in data science, statistics, or related fields |
| Work Environment | Deploying models in production, real-time data processing | Data analysis, model development, research |
| Industry Usage | AI product deployment, software companies | Research institutions, tech firms, consulting |
ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.
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8.0
Based on 409 frontline employees who took The Breakroom Quiz
136th of 540 rated manufacturers
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 it
ML 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.
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.
Build and manage RAG pipelines using vector databases (e.g., Azure Cognitive Search, Redis, FAISS) and orchestrate with tools like LangChain 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).
Use Terraform to automate provisioning of Azure resources, ensuring consistent and compliant environments for data science and engineering teams.
Integrate automated testing, linting, monitoring, and rollback mechanisms into the ML deployment pipeline.
Collaboration & Enablement
Work closely with Data Scientists, Cloud Engineers, and Product Teams to deliver production-ready AI features.
Contribute to solution architecture for real-time and batch AI use cases, including conversational AI, enterprise search, and summarization tools powered by LLMs.
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.
Strong experience deploying machine learning models on Azure using Azure ML and Azure DevOps.
Proven experience managing infrastructure as code with Terraform in production environments.
Technical Proficiency
Proficiency in Python (PyTorch, Transformers, LangChain) and Terraform, with scripting experience in Bash or PowerShell.
Experience with Docker and Kubernetes, especially within Azure (AKS).
Familiarity with CI/CD principles, model registry, and ML artifact management using Azure ML and Azure DevOps Pipelines.
Working knowledge of vector databases, caching strategies, and scalable inference architectures.
Soft Skills & Mindset
Systems thinker who can design, implement, and improve robust, automated ML systems.
Excellent communication and documentation skills-capable of bridging platform and data science teams.
Strong problem-solving mindset with a focus on delivery, reliability, and business impact.
Preferred Qualifications
Experience with LLMOps, prompt orchestration frameworks (LangChain, Semantic Kernel), and open-weight model deployment.
Exposure to smart buildings, IoT, or edge-AI deployments.
Understanding of governance, privacy, and compliance concerns in enterprise GenAI use cases.
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, andabilities of the applicant, internal equity, location and alignment with market data.) This position includes acompetitive benefits package. For details, please visit the About Us tab on the Johnson Controls Careers siteat 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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Johnson Controls is a world leader in smart buildings, creating safe, healthy and sustainable spaces. For nearly 140 years, we’ve made buildings better and now we’re transforming them again with our award-winning digital technologies and services. We’re using artificial intelligence and data driven solutions to give you deeper insight into your building’s health, sustainability and performance. It’s changing the way we design, operate and maintain indoor environments and driving to a new era of autonomous buildings. We deliver the blueprint of the future for industries such as healthcare, schools, data centers, airports, stadiums, hotels, manufacturing and beyond through OpenBlue, our comprehensive suite of connected solutions. Johnson Controls offers the world’s largest portfolio of building technology, software and services. Supported by a team of more than 100,000 dedicated employees working across 150 countries, we’re helping customers achieve their sustainability goals and power their mission.
Machinery manufacturing, water transportation, public safety statistics centers and offices and manufacturing
10,000+ Employees
Milwaukee, WI, US