Entry Level AI Research Engineer Jobs
New grad ai research engineer jobs are open to recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio of projects or internship work often carries more weight than a long resume. Most openings are on-site roles across Technology & Software, Electronics & Hardware, and Education, with employers like TikTok, Distyl, and JPMorganChase hiring at this level now.
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Showing 5 of 43+ Entry Level AI Research 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 JobsEntry Level AI Research Engineer Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software23
- Electronics & Hardware5
- Education2
- Automotive2
- Artificial Intelligence2
Entry Level AI Research Engineer Jobs: Frequently Asked Questions
How do I get an entry level ai research engineer job?
Employers at this level look for hands-on evidence of research ability: published or preprint papers, open-source contributions, and project work involving model training, evaluation, or experimental design. A strong GitHub profile and familiarity with frameworks like PyTorch or JAX matter more than years on a resume. Internship experience at a lab or tech company is a significant edge, and a master's or PhD opens additional doors at research-focused employers.
Which companies hire entry level ai research engineers?
Companies hiring entry level ai research engineers right now include TikTok, Distyl, and JPMorganChase, based on current listings on Migrate Mate as of November 2026. Hiring at this level comes from a mix of large technology companies running dedicated research labs, AI-native startups building foundation models, and enterprise companies integrating applied research into product teams.
Are there remote entry level ai research engineer jobs?
Yes, though most entry level research roles lean on-site or hybrid due to lab access and team collaboration expectations. About 31% of entry level ai research engineer openings are remote or hybrid as of November 2026, so fully remote options exist but are less common at this level than in software engineering broadly.
Are these new grad ai research engineer jobs?
Yes, the listings here include new grad, recent graduate, and junior ai research engineer roles. A posting is typically new-grad friendly when it welcomes zero to two years of experience, counts internships or research assistantships toward that requirement, or accepts a strong portfolio in place of professional history. Look for language like "new graduates encouraged to apply" or "research internship experience considered."
Which industries hire the most entry level ai research engineers?
Entry Level ai research engineer roles concentrate in Technology & Software, Electronics & Hardware, and Education, based on current listings on Migrate Mate as of November 2026. These sectors drive hiring at this level because they are actively building or scaling AI capabilities and need early-career researchers to support experimentation, benchmarking, and model development alongside senior staff.