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Data Curation Ai Machine Learning Jobs (NOW HIRING)

OneBlood

AI & Machine Learning Engineer

Saint Petersburg, FL

$105K - $127K/yr

... AI) and Machine Learning (ML) projects across the organization. Works with cross-functional teams ... Designs, builds, and maintains robust data pipelines to collect, clean, and transform data from ...

OneBlood

AI & Machine Learning Engineer

Saint Petersburg, FL · On-site

$105K - $127K/yr

... AI) and Machine Learning (ML) projects across the organization. Works with cross-functional teams ... Designs, builds, and maintains robust data pipelines to collect, clean, and transform data from ...

Lightspeed

AI & Machine Learning Engineer

Northbrook, IL · On-site

$100 - $130/hr

As an AI & Machine Learning Engineer, you will design, build, and deploy the intelligent systems ... Build predictive maintenance models using sensor data to anticipate equipment failures * Implement ...

Triwill Group

Staff Data Scientist

San Francisco, CA · On-site

$220 - $280/hr

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

Veryon

Software Engineer - AI & Machine Learning

About the Role The Software Engineer - AI & Machine Learning is responsible for designing ... Design, optimize, and maintain SQL databases , queries, and data models that support large-scale ...

Heartflow

Staff Data Scientist

San Francisco, CA · On-site

$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 ...

Eve

Machine Learning Engineer

San Mateo, CA · On-site

AI at Eve isn't a feature - it's the foundation. We're hiring an Machine Learning Engineer as the ... You'll own the full stack of applied ML - from data curation to evaluation and production ...

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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 Aug 14, 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?

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.

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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 13% Internship, 62% Full Time, and 25% Contract. Highlights an 100% In-person job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Gen AI / Machine Learning Engineer

AIToolboard

Washington, DC • On-site

$120 - $180/hr

Other

Posted 9 days ago

Job description

/Gen AI / Machine Learning Engineer# Gen AI / Machine Learning EngineerAptonetUSContractor## About the RoleGen AI / Machine Learning Engineer (NLP Focus) Location: Washington, DC (Onsite) Work Authorization: Must be authorized to work in the U.S. Clearance: Ability to obtain Public Trust or higher (if applicable)Role OverviewWe are seeking a highly skilled Generative AI / Machine Learning Engineer with strong expertise in Natural Language Processing (NLP) to design, develop, and deploy AI-driven solutions. This role will focus on building scalable ML systems, fine-tuning large language models (LLMs), and implementing NLP pipelines that power enterprise applications.The ideal candidate combines strong theoretical ML knowledge with hands-on engineering experience in modern AI frameworks and cloud-based ML infrastructure.Key Responsibilities• Design, develop, and deploy NLP and Generative AI solutions in production environments• Fine-tune and optimize Large Language Models (LLMs) for domain-specific use cases• Build and maintain ML pipelines for data ingestion, preprocessing, training, and inference• Develop prompt engineering strategies and evaluate model performance• Implement Retrieval-Augmented Generation (RAG) architectures• Work with structured and unstructured text datasets• Conduct model evaluation, error analysis, and performance tuning• Collaborate with data engineers and software teams to integrate AI models into applications• Ensure responsible AI practices including bias mitigation, explainability, and governance• Maintain documentation and contribute to AI best practices and architecture standardsRequired Qualifications• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or related field• 5+ years of experience in Machine Learning or AI engineering• 3+ years of hands-on experience with NLP• Strong programming skills in Python• Experience with ML frameworks such as:• PyTorch• TensorFlow• Scikit-learn• Experience working with:• Hugging Face Transformers• OpenAI / LLM APIs• LangChain or similar orchestration frameworks• Experience building and deploying models in cloud environments (AWS, Azure, or GCP)• Knowledge of vector databases (e.g., Pinecone, FAISS, Weaviate)• Strong understanding of:• Embeddings• Tokenization• Text classification• Named Entity Recognition (NER)• Sentiment analysis• Semantic search• Experience with REST APIs and microservices architecture• Familiarity with CI/CD pipelines for ML deploymentPreferred Qualifications• Experience with:• RAG architectures• LLM fine-tuning (LoRA, PEFT, etc.)• Distributed training• MLOps tools (MLflow, Kubeflow, SageMaker)• Experience working in regulated or government environments• Exposure to AI governance and compliance frameworks• Experience handling sensitive or classified datasetsNice to Have• Knowledge of reinforcement learning from human feedback (RLHF)• Experience building chatbots, copilots, or AI assistants• Experience with knowledge graphs• Familiarity with Kubernetes and containerization### Apply for this PositionFill out the form below to apply for this roleLocationUS #J-18808-Ljbffr

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