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Data Curation Ai Machine Learning Jobs (NOW HIRING)

Staxa Technologies

AI engineer

Minneapolis, MN · On-site

$119K - $143K/yr

Job Overview We are seeking an experienced AI / Machine Learning Engineer to design, build, and ... You will own the lifecycle of our AI features, from initial data curation and model selection to ...

Elevance Health

AI Machine Learning Scientist

Atlanta, GA · On-site +1

AI Machine Learning Scientist AI Machine Learning Scientist Location: This role requires associates ... Will work closely with engineering, product, data science, and business teams to translate complex ...

Elevance Health

AI Machine Learning Scientist

Tampa, FL · On-site +1

AI Machine Learning Scientist AI Machine Learning Scientist Location: This role requires associates ... Will work closely with engineering, product, data science, and business teams to translate complex ...

Elevance Health

AI Machine Learning Scientist

Tampa, FL · On-site +1

AI Machine Learning Scientist Location: This role requires associates to be in-office 1 day per ... Will work closely with engineering, product, data science, and business teams to translate complex ...

Heartflow

Staff Data Scientist

San Francisco, CA · Hybrid

$220K - $280K/yr

Advanced Data Curation & Management: Develop comprehensive data curation strategies for ... AI & Medical Imaging: Expertise in deep learning and machine learning models in production. Strong ...

Merican

AI / Machine Learning Engineer

PA · On-site

AI / Machine Learning Engineer (Contract) Location: Philadelphia, PA or Charlotte, NC Duration: 6 ... Integrate AI solutions with enterprise applications, APIs, and data platforms. * Optimize model ...

CyberMedia Technologies

AI / Machine Learning Engineer

$117K - $140K/yr

As an AI/ML Engineer for CTEC, you will develop Agentic AI systems designed to automate and ... Design and evaluate machine learning models that support both data-driven predictions and symbolic ...

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All JobsData Curation Ai Machine Learning Jobs

Data Curation Ai Machine Learning information

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$44.5K

$129.7K

$177.5K

How much do data curation ai machine learning jobs pay per year?

As of Jul 4, 2026, the average yearly pay for data curation ai machine learning in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Curation AI Machine Learning Specialist, and why are they important?

To thrive as a Data Curation AI Machine Learning Specialist, you need strong data management skills, a background in computer science or data science, and experience with machine learning principles. Familiarity with programming languages like Python or R, data labeling tools, and database systems, as well as certifications in machine learning or data engineering, are typically required. Attention to detail, critical thinking, and effective communication stand out as essential soft skills for managing complex datasets and collaborating with cross-functional teams. These skills ensure high-quality, well-organized data that drives accurate machine learning models and reliable AI outcomes.

What is a Data Curation AI/Machine Learning specialist?

A Data Curation AI/Machine Learning specialist is a professional who manages, organizes, and prepares large datasets to be used in artificial intelligence and machine learning projects. They ensure that data is accurate, relevant, and accessible, often cleaning and labeling data so it can be effectively used to train machine learning models. Their role bridges the gap between raw data sources and the teams building AI solutions, enabling more reliable and efficient model development. They may also work with data governance, privacy, and compliance issues to ensure data quality and security.

What are some common challenges faced by data curation professionals working in AI and machine learning projects?

One of the key challenges data curation specialists encounter in AI and machine learning is ensuring the quality and consistency of large, diverse datasets. This often involves dealing with missing, incomplete, or biased data, which can impact model performance. Additionally, data curators must navigate evolving data privacy regulations and work closely with data scientists, engineers, and domain experts to align data preparation with project goals. Effective communication and a meticulous approach are crucial for maintaining data integrity and supporting robust machine learning outcomes.

What is the difference between Data Curation Ai Machine Learning vs Data Analyst?

AspectData Curation Ai Machine LearningData Analyst
Primary FocusPreparing and managing data for AI and ML modelsAnalyzing data to generate business insights
Skills RequiredData management, programming, understanding of AI/ML algorithmsStatistical analysis, data visualization, Excel, SQL
Tools UsedPython, R, SQL, data cleaning toolsExcel, Tableau, SQL, statistical software
Work EnvironmentData science teams, AI/ML projects, tech companiesBusiness departments, analytics teams, consulting firms

While Data Curation Ai Machine Learning specialists focus on preparing data for AI and machine learning models, Data Analysts interpret data to support business decisions. Both roles require strong data skills but differ in their primary objectives and tools used.

More about Data Curation Ai Machine Learning jobs
What cities are hiring for Data Curation Ai Machine Learning jobs? Cities with the most Data Curation Ai Machine Learning job openings:
What states have the most Data Curation Ai Machine Learning jobs? States with the most job openings for Data Curation Ai Machine Learning jobs include:
What job categories do people searching Data Curation Ai Machine Learning jobs look for? The top searched job categories for Data Curation Ai Machine Learning jobs are:
Data Curation Ai Machine Learning jobs near you
Infographic showing various Data Curation Ai Machine Learning job openings in the United States as of June 2026, with employment types broken down into 1% Internship, 59% Full Time, 39% Part Time, and 1% Temporary. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

AI engineer

Staxa Technologies

Minneapolis, MN • On-site

$119K - $143K/yr

Other

Posted 23 days ago

Job description

Job Overview
We are seeking an experienced AI / Machine Learning Engineer to design, build, and deploy production-grade AI systems. In this role, you will bridge the gap between AI research and scalable software engineering. You will own the lifecycle of our AI features, from initial data curation and model selection to cloud deployment and continuous monitoring.
Core Responsibilities
  • Model Development: Design, train, and fine-tune machine learning models, including Large Language Models (LLMs) and predictive algorithms.
  • System Architecture: Build robust, scalable, and secure data pipelines and AI infrastructures to support real-time inference.
  • Production Deployment: Deploy models to cloud environments using modern MLOps practices, ensuring high availability and low latency.
  • Optimization: Monitor system performance, optimize inference costs, and debug complex model behaviors in production.
  • Collaboration: Work closely with Product Managers, Data Engineers, and Frontend developers to integrate AI features into user-facing products.
Required Technical Skills
  • Programming: Advanced proficiency in Python (knowledge of C++ or Go is a plus).
  • Frameworks: Deep hands-on experience with PyTorch or TensorFlow.
  • GenAI / LLM Stack: Proven experience with libraries like Hugging Face, LangChain, or LlamaIndex, and working with vector databases (e.g., Pinecone, Milvus, Qdrant).
  • Data Engineering: Strong competency in SQL and experience handling large datasets using tools like pandas or Apache Spark.
  • MLOps & Cloud: Hands-on experience with cloud providers (AWS, Google Cloud Platform, or Azure) and containerization tools like Docker and Kubernetes.
Qualifications & Experience
  • Education: Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Mathematics, or a highly quantitative field.
  • Experience: 5+ years of software engineering experience, with at least 3+ years dedicated to building and deploying AI/ML models in a commercial production environment.
  • Portfolio: A proven track record of shipping AI features that directly impacted business metrics or user experience.
 
 
 
 
 
 
 
 

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