Entry Level Applied AI Engineer Jobs
New grad applied ai engineer jobs are open to recent graduates and entry level candidates with little to no experience, where a strong portfolio or internship project can outweigh a long resume at this stage. Most openings are on-site roles across Technology & Software, Science & Research, and Consulting & Professional Services, with employers like Distyl, Ramp, and OpenAI hiring at this level now.
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SUMMARY
Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Multifaceted, amazing people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same passion for innovation that goes into our products also applies to our practices, strengthening our commitment to leave the world better than we found it. Join us in this truly exciting era of Artificial Intelligence to help deliver the next groundbreaking Apple products & experiences! We are continuously advancing the state of the art in Computer Vision and Machine Learning, touching all aspects of language and multimodal foundation models, from data collection, data curation to modeling, evaluation and deployment. As a member of our dynamic group, you will have the unique and rewarding opportunity to craft upcoming research directions in the field of multimodal foundation models that will inspire future Apple products. You will be working alongside highly accomplished and deeply technical scientists and engineers to develop pioneering solutions for challenging problems. This is a unique opportunity to be part of what forms the future of Apple products that will touch the lives of many people. We (Multimodal Intelligence Team) are looking for an Applied AI Scientist to work on the field of Generative AI and multimodal foundation models. Our team has an established track record of shipping features that leverage multiple sensors, such as FaceID, RoomPlan and hand tracking in VisionPro, as well as a strong research presence in the multimodal AI community. Our publications span multimodal pre-training, vision-language models, video-language models, and multimodal alignment. We are focused on building experiences that demonstrate the power of our sensing hardware as well as large foundation models.
DESCRIPTION
This position requires a highly motivated person who wants to help us bridge the gap between research advances and practical applications in generative AI and multimodal foundation models. You will be responsible for evaluating and adapting emerging research, conducting applied research experiments, and working with engineering teams to transform promising approaches into robust solutions, taking into account future hardware design and product needs. In addition, you will have an opportunity to engage and collaborate with several teams across Apple to deliver the best products.
MINIMUM QUALIFICATIONS
- Experience in deep learning with demonstrated work in at least one area of multimodal systems (e.g. vision, language, video, etc.).
- Proficiency in Python and in a modern deep learning framework such as PyTorch or JAX.
- Experience with rapid prototyping, reproduction, and validation of research ideas.
- Master's or equivalent practical experience, in Computer Science, Computer Vision, Machine Learning, or related technical field.
PREFERRED QUALIFICATIONS
- PhD, or equivalent practical experience, in Computer Science, Machine Learning, or a related technical field.
- Demonstrated expertise in deep learning, with either: A publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, COLM, etc), or a strong track record of applying deep learning techniques to real-world products.
- Experience with foundation models (language or multimodal).
- Familiarity with large-scale data pipelines, including data curation, preprocessing, and efficient storage.
- Experience fine-tuning or optimizing large models for production deployment.
- Experience applying foundation models to build autonomous or semi-autonomous agents, including planning, task decomposition, and multi-step reasoning.
- Familiarity with privacy-preserving or on-device machine learning.
- Ability to work effectively in a multi-functional, collaborative environment.
COMPENSATION
- Base pay range for this role is between $150,400 and $277,600, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.
At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
Apple accepts applications to this posting on an ongoing basis.
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Entry Level Applied AI Engineer Jobs: Frequently Asked Questions
How do I get an entry level applied ai engineer job?
Employers hiring at the entry level look for hands-on evidence of applied skills over credentials alone. A portfolio of projects using large language models, computer vision pipelines, or model deployment work gives you a concrete edge. Coursework in machine learning, proficiency in Python and common ML frameworks, and any internship or capstone experience building production-ready AI tools all strengthen your application significantly at this stage.
Which companies hire entry level applied ai engineers?
Companies hiring entry level applied ai engineers right now include Distyl, Ramp, and OpenAI, based on current listings on Migrate Mate as of November 2026. Hiring at this level comes from a mix of AI-native startups, technology consultancies, and large enterprises building or expanding internal AI teams.
Are there remote entry level applied ai engineer jobs?
Yes, though most entry level roles still favor in-person or hybrid arrangements. About 44% of entry level applied ai engineer openings are remote or hybrid as of November 2026, so candidates open to on-site work will find a wider pool of opportunities at this stage.
Are these new grad applied ai engineer jobs?
Yes, these listings include new grad, recent graduate, and junior applied ai engineer roles. A posting is new-grad friendly when it welcomes zero to two years of experience, treats internships or academic projects as qualifying background, or accepts a strong portfolio in place of full-time professional history. Searching for junior or recent graduate roles surfaces the same pool.
Which industries hire the most entry level applied ai engineers?
Entry Level applied ai engineer roles concentrate in Technology & Software, Science & Research, and Consulting & Professional Services, based on current listings on Migrate Mate as of November 2026. These sectors are investing heavily in building and integrating AI systems, which creates steady demand for engineers who can work on model development, evaluation, and deployment from an early career stage.