Entry Level AI Engineer Jobs
New grad ai engineer jobs are open to recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio or hands-on internship work can matter more than a long resume. Most openings mix on-site, remote, and hybrid settings across Technology & Software, Electronics & Hardware, and Consulting & Professional Services, with employers like Capital One, TikTok, and OpenAI hiring at this level now.
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Showing 5 of 128+ Entry Level AI Engineer 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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Find Entry Level AI Engineer JobsEntry Level AI Engineer Job Market
Who's Hiring
- Capital One11
- TikTok10
- OpenAI6
- Hewlett Packard Enterprise | HPE4
- Ramp3
Top Industries Hiring
- Technology & Software62
- Electronics & Hardware10
- Consulting & Professional Services10
- Science & Research8
- Artificial Intelligence7
Entry Level AI Engineer Jobs: Frequently Asked Questions
How do I get an entry level ai engineer job?
Entry level ai engineer roles reward candidates who can show applied work, not just coursework. Build a portfolio with personal or open-source projects that demonstrate model training, data pipelines, or deployed applications. Familiarity with Python, PyTorch or TensorFlow, and basic machine learning concepts gives you a real edge. Internship experience at any scale, even a semester-long project, signals you can work in a professional environment.
Which companies hire entry level ai engineers?
Companies hiring entry level ai engineers right now include Capital One, TikTok, and OpenAI, based on current listings on Migrate Mate as of November 2026. Hiring at this level comes from a wide range of employers, including large tech firms, enterprise software companies, defense and government contractors, and early-stage startups building AI-native products.
Are there remote entry level ai engineer jobs?
Yes, remote and hybrid options exist at this level, though on-site roles are also common. About 28% of entry level ai engineer openings are remote or hybrid as of November 2026, so candidates who need location flexibility have real options. Filtering by work setting on Migrate Mate lets you focus only on the openings that match your situation.
Are these new grad ai engineer jobs?
Yes, the listings here include new grad, recent graduate, and junior ai engineer roles. A new grad-friendly posting typically welcomes zero to two years of experience and counts internships, capstone projects, or a strong portfolio toward that threshold. If a job description asks for hands-on work rather than years on a resume, it is generally open to new graduates entering the field for the first time.
Which industries hire the most entry level ai engineers?
Entry Level ai engineer roles concentrate in Technology & Software, Electronics & Hardware, and Consulting & Professional Services, based on current listings on Migrate Mate as of November 2026. These sectors drive hiring at this level because they are actively building or expanding AI-powered products and internal tooling, which creates consistent demand for junior engineers who can contribute to model development, data work, and integration projects.