Entry Level AI Data Specialist Jobs
New grad ai data specialist jobs are open to recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio or internship project can carry more weight than a long resume. Most openings are Technology & Software, Energy, and Education roles with varying on-site, remote, and hybrid arrangements, and employers like JPMorganChase, C Spire, and Qualcomm are hiring at this level now.
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Showing 5 of 12+ Entry Level AI Data Specialist jobs
Job Description: AI/ML Engineer
Full-Time Position
IT – Technology
Job Title: Artificial Intelligence / Machine Learning Engineer
Department: Information Technology / Engineering
Experience: 2–5 Years (depending on company requirements)
Job Location: USA / Remote / Hybrid
1. Job Summary
We are looking for a skilled AI/ML Engineer to design, develop, and implement artificial intelligence and machine learning solutions. The ideal candidate will work with large datasets, build predictive models, develop intelligent applications, and improve existing systems using machine learning algorithms and deep learning techniques.
2. Roles and Responsibilities
- Design, develop, and deploy machine learning models and AI-based applications.
- Collect, clean, process, and analyze large datasets.
- Develop predictive models using machine learning algorithms.
- Implement deep learning techniques for complex data analysis.
- Work with Natural Language Processing (NLP) and computer vision technologies.
- Build and optimize AI models to improve accuracy and performance.
- Collaborate with data scientists, software developers, and engineering teams.
- Integrate AI/ML models into existing applications and business systems.
- Monitor deployed models and improve their performance.
- Research emerging AI technologies and industry trends.
3. Required Technical Skills
- Programming Languages: Python, R, Java, C++.
- Machine Learning: Scikit-learn, TensorFlow, PyTorch, Keras.
- Data Processing: Pandas, NumPy, SQL.
- Deep Learning: Neural Networks, CNN, RNN.
- AI Technologies: Generative AI, Large Language Models (LLMs), NLP.
- Cloud Platforms: AWS, Microsoft Azure, Google Cloud.
- Data Visualization: Tableau, Power BI, Matplotlib.
- Tools: Jupyter Notebook, Git, Docker, Kubernetes.
4. Educational Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, Machine Learning, or a related field.
- Strong understanding of mathematics, statistics, and computer science fundamentals.
5. Preferred Skills
- Experience developing and deploying AI/ML models.
- Knowledge of cloud-based machine learning platforms.
- Understanding of MLOps and model lifecycle management.
- Experience working with large-scale datasets.
- Strong analytical, problem-solving, and communication skills.
6. Key Performance Indicators (KPIs)
- Model accuracy and prediction performance.
- Efficiency of AI/ML model deployment.
- Reduction in processing time.
- Quality and reliability of developed AI solutions.
- Successful integration of AI models into business applications.
Job Description: AI/ML Engineer
Full-Time Position
IT – Technology
Job Title: Artificial Intelligence / Machine Learning Engineer
Department: Information Technology / Engineering
Experience: 2–5 Years (depending on company requirements)
Job Location: USA / Remote / Hybrid
1. Job Summary
We are looking for a skilled AI/ML Engineer to design, develop, and implement artificial intelligence and machine learning solutions. The ideal candidate will work with large datasets, build predictive models, develop intelligent applications, and improve existing systems using machine learning algorithms and deep learning techniques.
2. Roles and Responsibilities
- Design, develop, and deploy machine learning models and AI-based applications.
- Collect, clean, process, and analyze large datasets.
- Develop predictive models using machine learning algorithms.
- Implement deep learning techniques for complex data analysis.
- Work with Natural Language Processing (NLP) and computer vision technologies.
- Build and optimize AI models to improve accuracy and performance.
- Collaborate with data scientists, software developers, and engineering teams.
- Integrate AI/ML models into existing applications and business systems.
- Monitor deployed models and improve their performance.
- Research emerging AI technologies and industry trends.
3. Required Technical Skills
- Programming Languages: Python, R, Java, C++.
- Machine Learning: Scikit-learn, TensorFlow, PyTorch, Keras.
- Data Processing: Pandas, NumPy, SQL.
- Deep Learning: Neural Networks, CNN, RNN.
- AI Technologies: Generative AI, Large Language Models (LLMs), NLP.
- Cloud Platforms: AWS, Microsoft Azure, Google Cloud.
- Data Visualization: Tableau, Power BI, Matplotlib.
- Tools: Jupyter Notebook, Git, Docker, Kubernetes.
4. Educational Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, Machine Learning, or a related field.
- Strong understanding of mathematics, statistics, and computer science fundamentals.
5. Preferred Skills
- Experience developing and deploying AI/ML models.
- Knowledge of cloud-based machine learning platforms.
- Understanding of MLOps and model lifecycle management.
- Experience working with large-scale datasets.
- Strong analytical, problem-solving, and communication skills.
6. Key Performance Indicators (KPIs)
- Model accuracy and prediction performance.
- Efficiency of AI/ML model deployment.
- Reduction in processing time.
- Quality and reliability of developed AI solutions.
- Successful integration of AI models into business applications.
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Top Industries Hiring
- Technology & Software
- Energy
- Education
- Insurance
- Automotive
Entry Level AI Data Specialist Jobs: Frequently Asked Questions
How do I get an entry level ai data specialist job?
Entry level ai data specialist employers look for hands-on evidence of your skills, not years on a resume. Build a portfolio with real projects: data cleaning pipelines, model training notebooks, or annotation quality work. Familiarity with Python, basic machine learning concepts, and tools like Label Studio or Scale AI gives you a concrete edge. Internship experience, even a short one, signals you can work inside a production workflow.
Which companies hire entry level ai data specialists?
Companies hiring entry level ai data specialists right now include JPMorganChase, C Spire, and Qualcomm, based on current listings on Migrate Mate as of November 2026. Hiring at this level comes from a mix of AI-native startups building training datasets, large tech firms expanding their model development teams, and data services companies that onboard junior specialists in volume.
Are there remote entry level ai data specialist jobs?
Yes, remote and hybrid options are common at this level. About 25% of entry level ai data specialist openings are remote or hybrid as of November 2026, reflecting how much of this work, including data labeling, quality review, and annotation, can be done asynchronously from anywhere. On-site roles do exist, particularly at companies that handle sensitive or proprietary training data.
Are these new grad ai data specialist jobs?
Yes, these listings include new grad, recent graduate, and junior ai data specialist roles. A posting is new-grad friendly when it welcomes zero to two years of experience, accepts internships or academic projects in place of full-time history, or lists a portfolio as an acceptable credential. If the job description asks for demonstrated skills rather than years, it is a strong fit for a new grad applying for the first time.
Which industries hire the most entry level ai data specialists?
Entry Level ai data specialist roles concentrate in Technology & Software, Energy, and Education, based on current listings on Migrate Mate as of November 2026. Those sectors drive hiring at this level because they are actively building or expanding AI and machine learning pipelines that depend on well-labeled, high-quality training data, creating consistent demand for junior specialists who can support that work.