Entry Level Staff AI Product Manager Jobs
New grad staff ai product manager jobs are open to recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio of AI-adjacent coursework, internship work, or a capstone project can carry more weight than a long resume. Most openings are across Technology & Software, Energy, and Education, with employers like JPMorganChase, Angi, and C Spire hiring at this level now.
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Showing 5 of 13+ Entry Level Staff AI Product Manager 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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Who's Hiring
Top Industries Hiring
- Technology & Software
- Energy
- Education
- Insurance
- Automotive
Entry Level Staff AI Product Manager Jobs: Frequently Asked Questions
How do I get an entry level staff ai product manager job?
Employers hiring entry level staff ai product managers look for candidates who can demonstrate familiarity with AI product concepts, user research basics, and structured problem-solving. A capstone project, internship, or side project that shows you can define a problem, prioritize features, and work with engineers or data teams will give you a real edge. Certifications in product management or AI fundamentals also strengthen an application at this stage.
Which companies hire entry level staff ai product managers?
Companies hiring entry level staff ai product managers right now include JPMorganChase, Angi, and C Spire, based on current listings on Migrate Mate as of November 2026. Hiring at this level comes from a mix of AI-native startups, enterprise technology teams, and product-led companies building out early-career pipelines for roles that sit at the intersection of AI and product strategy.
Are there remote entry level staff ai product manager jobs?
Yes, though availability varies by employer and team structure. About 33% of entry level staff ai product manager openings are remote or hybrid as of November 2026, so there are real options for candidates who need location flexibility. Many hybrid roles are a practical starting point for new grads since they offer in-person onboarding alongside schedule flexibility.
Are these new grad staff ai product manager jobs?
Yes, many of the staff ai product manager openings listed here are new grad and junior roles that welcome candidates with zero to two years of experience, including recent graduates and career changers. A posting is typically new-grad friendly when it lists a bachelor's degree as the primary requirement, accepts internships or coursework in place of full-time experience, or explicitly invites a portfolio rather than a work history.
Which industries hire the most entry level staff ai product managers?
Entry Level staff ai product manager roles concentrate in Technology & Software, Energy, and Education, based on current listings on Migrate Mate as of November 2026. Those sectors drive entry level hiring because they are actively scaling AI-powered products and need junior product talent who can work closely with engineering and research teams from an early career stage.