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Data Curation Ai Machine Learning Jobs (NOW HIRING)

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 ...

Metas Solutions

AI/Machine Learning Engineer

Decatur, GA · On-site

$95K - $130K/yr

... data quality, curation, and documentation standards in collaboration with cross-functional AI teams ... deploying machine learning models8+ years of experience with Generative AI, LLMs, or RAG ...

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 ...

USAA

Senior AI & Machine Learning Engineer

San Antonio, TX · On-site +1

$143K - $273K/yr

Extensive data engineering experience. * Experience with end to end delivering of machine learning and AI/GenAI solutions that includes building, integrating, and optimizing data pipelines; curating ...

USAA

Senior AI & Machine Learning Engineer

San Antonio, TX · On-site +1

$143K - $273K/yr

Extensive data engineering experience. * Experience with end to end delivering of machine learning and AI/GenAI solutions that includes building, integrating, and optimizing data pipelines; curating ...

USAA

Senior AI & Machine Learning Engineer

San Antonio, TX · On-site

$143K - $273K/yr

Extensive data engineering experience. * Experience with end to end delivering of machine learning and AI/GenAI solutions that includes building, integrating, and optimizing data pipelines; curating ...

USAA

Senior AI & Machine Learning Engineer

San Antonio, TX · On-site +1

$143K - $273K/yr

Extensive data engineering experience. * Experience with end to end delivering of machine learning and AI/GenAI solutions that includes building, integrating, and optimizing data pipelines; curating ...

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

As of Sep 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 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 the key skills and qualifications needed to thrive as a data curation AI machine learning specialist?

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 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.

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Data Curation Ai Machine Learning jobs near you
Infographic showing various Data Curation Ai Machine Learning job openings in the United States as of August 2026, with employment types broken down into 84% Full Time, 8% Part Time, and 8% Contract. Highlights an 67% In-person, 8% Hybrid, and 25% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

AI / Machine Learning Engineer

CyberMedia Technologies

Remote

Full-time

Re-posted 5 days ago

Job description

We are seeking to hire a AI/Machine Learning Engineer to our team!

Role Overview:
As an AI/ML Engineer for CTEC, you will develop Agentic AI systems designed to automate and optimize health benefits determinations for the Office of Personnel Management (OPM). Unlike traditional "black-box" models, your work will focus on marrying the reasoning capabilities of Large Language Models (LLMs) with deterministic, rule-driven patterns to ensure accuracy, auditability, and compliance in complex decision-making workflows.

Duties and Responsibilities:

  • Agentic System Architecture: Design and deploy autonomous AI agents capable of multi-step reasoning, tool-use, and self-correction to navigate complex federal benefit policies.
  • Deterministic Logic Integration: Develop "Guardrail" layers that synchronize probabilistic LLM outputs with rigid business rules, ensuring benefit determinations adhere strictly to legal and regulatory frameworks.
  • RAG & Knowledge Engineering: Implement advanced Retrieval-Augmented Generation (RAG) solutions, utilizing layout-aware parsing to extract information from dense manuals/documentation and unstructured data.
  • Hybrid Model Development: Design and evaluate machine learning models that support both data-driven predictions and symbolic/rule-based automation.
  • MLOps & Agent Monitoring: Deploy models into cloud environments with a focus on LLM-specific observability (tracing reasoning loops, monitoring for hallucinations, and detecting data drift in logic).
  • Auditability & Explainability: Ensure every AI-driven determination has a clear, human-readable "audit trail" or reasoning chain that justifies the outcome based on source documentation.
  • Collaboration: Work alongside solution architects and business stakeholders to translate complex health insurance policies into executable AI logic.

Skills & Work Experience:

  • Professional Experience: 5+ years in Machine Learning or Data Science, with at least 2 years of hands-on experience with LLM orchestration and Generative AI frameworks.
  • Agentic Frameworks: Proficiency with tools such as LangChain, LangGraph, CrewAI, or Semantic Kernel for building multi-step agent workflows.
  • Core Development: Strong proficiency in Python and experience with standard frameworks (PyTorch, TensorFlow, or Scikit-learn)
  • Data Engineering: Strong SQL skills and experience with distributed data processing (Spark/PySpark) to handle large-scale enterprise data.
  • Analytical Rigor: Ability to debug non-deterministic systems and implement rigorous evaluation frameworks (e.g., RAGAS, LLM-as-a-judge) data platforms.

Preferred:

  • Experience with Azure Machine Learning, Azure AI services, or similar cloud AI platforms.
  • Experience implementing Generative AI, LLM, or RAG-based solutions.
  • Experience supporting federal IT modernization or data transformation programs.
  • Familiarity with healthcare, insurance, or benefits administration data environments.
  • Experience applying data governance, privacy, and security best practices in AI/ML solutions.

Education:

Bachelor's degree in Computer Science, Data Science, Engineering, or a related discipline. Master's degree preferred. Equivalent professional experience will be considered in lieu of a degree.

Clearance:
Must be a U.S. citizen and be able to obtain an OPM Public Trust clearance.

Apply