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Ml Data Associate Jobs in Brookfield, WI (NOW HIRING)

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science ... AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI ...

Senior Forward Deployed Engineer- AWS

Milwaukee, WI · On-site

$103K - $141K/yr

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science ... AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI ...

Lead Forward Deployed Engineer - AWS

Milwaukee, WI · On-site

$101K - $133K/yr

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science ... AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI ...

... Associate - SAP Master Data Governance (MDG) - SnowPro Core / SnowPro Advanced - Databricks Certified Data Engineer / Data Analyst / ML - Proven leadership in data-driven strategies - Experience in ...

... Associate - SAP Master Data Governance (MDG) - SnowPro Core / SnowPro Advanced - Databricks Certified Data Engineer / Data Analyst / ML Travel Requirements Up to 80% Job Posting End Date The salary ...

... Associate - SAP Master Data Governance (MDG) - SnowPro Core / SnowPro Advanced - Databricks Certified Data Engineer/Data Analyst/ML - Proven leadership in data-driven strategies - Demonstrating ...

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Ml Data Associate information

See Brookfield, WI salary details

$54.4K

$64.4K

$122.1K

How much do ml data associate jobs pay per year?

As of Sep 7, 2026, the average yearly pay for ml data associate in Brookfield, WI is $64,411.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,900.00 and $56,300.00 per year, depending on experience, location, and employer.

What is an ml data associate?

ML Data Associates are professionals who support machine learning projects by preparing, labeling, and validating data used to train and evaluate algorithms. They often work with large datasets, ensuring data quality and accuracy, and may use specialized tools to annotate images, text, or audio. Their work is essential for enabling machine learning models to learn from high-quality, well-structured data, and they often collaborate with data scientists and engineers to optimize data pipelines.

What are the key skills and qualifications needed to thrive as an ml data associate?

To thrive as an ML Data Associate, you need strong analytical skills, attention to detail, and a solid understanding of data annotation or labeling, often supported by a degree in a technical field. Familiarity with data labeling tools, basic programming (such as Python), and experience working with machine learning platforms are typically required. Excellent communication, problem-solving abilities, and the capacity to work efficiently in teams are important soft skills. These skills ensure high-quality, accurately labeled datasets that are essential for training effective machine learning models.

What are some common challenges faced by ml data associates when labeling complex datasets, and how can they be effectively addressed?

ML Data Associates often encounter challenges with ambiguous data, inconsistent labeling guidelines, or rapidly evolving project requirements. To address these, it's important to maintain open communication with data scientists and project leads, ask clarifying questions, and participate in regular calibration sessions to ensure consistency. Utilizing annotation tools efficiently and staying up-to-date with best practices can also help manage complexity and improve label quality. Collaboration and feedback within the team are key to overcoming these challenges and ensuring high-quality datasets.

What is the difference between Ml Data Associate vs Data Analyst?

AspectML Data AssociateData Analyst
Required CredentialsTypically a degree in computer science, data science, or related field; familiarity with machine learning conceptsUsually a degree in statistics, mathematics, or business analytics; strong Excel and data visualization skills
Work EnvironmentTech companies, AI startups, or organizations focusing on machine learning projectsBusiness, finance, marketing, and consulting firms analyzing data for insights
Employer & Industry UsageUsed in industries developing AI models, machine learning pipelines, and data infrastructureCommon across industries for reporting, trend analysis, and strategic decision-making

While both roles involve working with data, ML Data Associates focus on preparing and managing data specifically for machine learning models, whereas Data Analysts interpret data to generate business insights. The roles overlap in data handling skills but differ in their end goals and technical focus.

How do I become an ML Data Associate?

To become an ML Data Associate, candidates typically need a high school diploma or equivalent, along with strong attention to detail and organizational skills. Familiarity with data management tools, basic understanding of machine learning concepts, and experience with data annotation or labeling are often required. Some roles may also require knowledge of programming languages like Python or experience with data annotation platforms.

What skills do you need for a machine learning data associate job?

A machine learning data associate needs strong analytical skills, attention to detail, and proficiency in data management tools like Excel, SQL, or Python. Knowledge of data cleaning, labeling, and basic understanding of machine learning concepts are also important for the role.

What are popular job titles related to Ml Data Associate jobs in Brookfield, WI?

For Ml Data Associate jobs in Brookfield, WI, the most frequently searched job titles are:

What job categories do people searching Ml Data Associate jobs in Brookfield, WI look for?

The top searched job categories for Ml Data Associate jobs in Brookfield, WI are:

What cities near Brookfield, WI are hiring for Ml Data Associate jobs?

Cities near Brookfield, WI with the most Ml Data Associate job openings:

Infographic showing various Ml Data Associate job openings in Brookfield, WI as of July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 13% Part Time, 1% Temporary, and 4% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $63,759 per year, or $30.7 per hour.

$85 - $107/hr

Other

Posted 5 days ago


Key responsibilities

  • Build and manage end‑to‑end ML/LLM pipelines on Azure using Azure DevOps for CI/CD, testing, and release automation.

  • Operationalize LLMs and generative AI solutions with a focus on automation, security, and scalability.

  • Design and manage infrastructure as code using Terraform, including provisioning compute clusters, storage, and networking.


Job description

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.

ResponsibilitiesML 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 (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
  • Design highly available and performant serving environments for LLM inference using Azure Kubernetes Service and Azure Functions or App Services.
  • Build and manage Retrieval Augmented Generation pipelines using vector databases (Azure Cognitive Search, Redis, FAISS) and orchestrate with tools like LangChain or Semantic Kernel.
  • Ensure security, logging, role‑based access control, 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
  • 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.
  • 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.
  • Systems thinker who can design, implement, and improve robust, automated ML systems.
  • Excellent communication and documentation skills.
  • 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 (Azure Solutions Architect, Azure AI Engineer, Terraform Associate) is a plus.
Salary & Benefits

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.

EEO Statement

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, please 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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