machine learning intern

Apple

Are you excited to tackle some of the most ambitious technical challenges in Apple Intelligence? Be involved in collaborating closely with our machine learning researchers, engineers, and data scientists? 
 
Together, you will orchestrate groundbreaking research initiatives and develop transformative products designed to build a significant impact for billions of users worldwide! 
 
As part of Apple&rsquo;s AI and Machine Learning org, we encourage and create groundbreaking technology for large-scale ML systems, computer vision, natural language processing, and multi-modal understanding and generation. 
 
The Data and Machine Learning Innovation (DMLI) team is looking for Machine Learning Engineer to explore new methods, challenge existing metrics or protocols, and develop new insightful practices that will change how we understand data and overcome real-world ML challenges. 
 
Description 
 
As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying state of the art research in ML to tackle complex data problems. 
 
The solutions you develop will significantly impact Apple Intelligence, future Apple products and the broader ML development ecosystem. 
 
You will work with a multidisciplinary team to actively participate in Apple Intelligence&rsquo;s data-model co-design and co-develop practice. 
 
Your responsibilities will extend to the design and development of a comprehensive data generation and curation framework for Apple Intelligence foundation models at Apple. 
 
You will also be responsible to build robust model evaluation pipelines, integral to the continuous improvement and assessment of Apple Intelligence foundation models. 
 
Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues. 
 
&quot;,&quot;responsibilities&quot;:&quot;Develop and implement techniques for creating high-quality synthetic datasets across a variety of domains, including vision, text, and audio data. 
 
Innovate and experiment with new approaches for synthetic data generation to improve the diversity, realism, and representativeness of datasets. 
 
Collaborate with multi-functional teams to understand data requirements and ensure that synthetic datasets are optimized for training foundation models. 
 
Crafting and implementing semi-supervised, self-supervised representation learning techniques for growing the power of both limited labeled data and large-scale unlabeled data. 
 
Develop pipelines and tools to automate synthetic data generation for large-scale AI experiments. 
 
Stay updated with the latest research and industry trends in synthetic data generation, foundational model training, and large-scale data engineering. 
 
Preferred Qualifications 
 
3+ years of experience with developing and evaluating ML applications, and demonstrated experience in understanding and improving data quality. 
 
Strong publication record in relevant conferences (e.g. CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, etc). 
 
Strong problem-solving and communication skills. 
 
Experience of multimodal large language model or image/video generation model training is a plus. 
 
Ph.D/MS degree in Machine Learning, Natural Language Processing, Computer Vision, Data Science, Statistics or related areas. 
 
Minimum Qualifications 
 
Demonstrated expertise in computer vision, natural language processing, and machine learning with a passion for data-centric machine learning. 
 
Deep understanding in multi-modal foundation models. 
 
Staying on top of emerging trends in generative AI and multi-modal LLM. 
 
Strong programming skills and hands-on experience using the following languages or deep learning frameworks: Python, PyTorch, or Jax. 
 
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. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $171,600 and $302,200, 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. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

AIML - Sr Machine Learning Engineer, Data and ML Innovation

Are you passionate about building extraordinary products and embracing state of art techniques? It's central to all that we do! The goal of the Apple Services GenAI &amp; ML Frameworks team is to take personalization, search, and more to the next level of intelligence and accuracy using advanced ML and statistical techniques. 
 
Description 
 
We work on a wide spectrum of approaches, including foundation modeling, deep learning, model compression, transfer learning, federated learning and more. We work on core machine learning algorithms and models to power personalization in an efficient and scalable manner. We also work on algorithmic approaches to conserve resources when delivering these models to our customers' devices. This position involves a wide variety of skills and innovation. This is a rare opportunity that sits at the state of the art of machine learning and software! 
 
Preferred Qualifications 
 
PhD in a quantitative field, including Computer Science, Maths, Statistics, Physics, etc. 
 
Minimum Qualifications 
 
BS/MS in a quantitative field, including Computer Science, Maths, Statistics, Physics, etc. 
 
2+ years of relevant work experience 
 
Proficient programming skills in Python 
 
Hands-on experience working with deep learning toolkits such as Jax, Tensorflow or PyTorch 
 
Proven track record in training or deployment of large models or building large-scale distributed systems 
 
Deep understanding of Deep Learning and Large Language Models (LLMs) 
 
Natural Language Processing 
 
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. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 and $258,100, 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. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Machine Learning Engineer, Apple Services Engineering

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other&rsquo;s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It&rsquo;s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you&rsquo;ll do more than join something - you&rsquo;ll add something. 
 
As part of Apple&rsquo;s central data annotation engineering team, you&rsquo;ll help build the next generation of AI-powered user experiences. Our work provides high-quality datasets and expert feedback to train machine learning models and evaluate their performance across all products and verticals. The team maintains and develops a global distributed system that captures insights from human domain experts and analysts worldwide, operating at a scale that few companies can match. We leverage cutting-edge human-in-the-loop algorithms to create and curate datasets through fine-tuned multi-step annotation workflows and near real-time data quality feedback signals. You&rsquo;ll tackle complex challenges in ML data quality at unprecedented scale while collaborating closely with AIML engineering teams across the company. From Siri to the Photos app, from iPhone to Vision Pro, you&rsquo;ll help bring innovative experiences to millions of users worldwide. 
 
Description 
 
This role focuses on enhancing the annotation quality capabilities of Apple's central data annotation platform. You'll work on a cloud-based system that supports machine learning model development across all Apple products. The position combines backend engineering with research and concept development to improve how we measure, monitor, and optimize annotation and ML dataset quality at scale. You'll be responsible for building systems that ensure high-quality training data while developing innovative approaches to quality assessment and feedback mechanisms. 
 
As part of a close-knit team of half a dozen engineers focused on annotation quality initiatives and embedded in an even larger team of fellow data annotation engineers, you'll collaborate on shared challenges and contribute to collective problem-solving efforts. The team works together on overlapping projects, combining individual expertise in backend and frontend engineering, statistics, and ML to advance the state of annotation quality measurement and optimization. You'll have the opportunity to learn from peers tackling similar technical problems while contributing your own insights to push the boundaries of what's possible in large-scale data quality assessment. 
 
Your contributions will directly impact the foundation of Apple's AI and machine learning capabilities, ensuring that models across the entire product ecosystem are trained on the highest quality data possible.&quot;,&quot;responsibilities&quot;:&quot;Develop and maintain backend services for annotation quality measurement and monitoring systems 
 
Design and implement statistical measures and algorithms to assess annotation quality across diverse datasets incl. both foundational model driven and traditional approaches 
 
Create automated quality feedback mechanisms that provide real-time insights to annotation teams 
 
Research and prototype new approaches for improving annotation consistency and accuracy 
 
Optimize and design efficient data pipelines for dataset/annotation quality metrics collection 
 
Preferred Qualifications 
 
5+ years of experience in data annotation, data quality, or related ML value chain roles 
 
Experience building and scaling web-based platforms for machine learning workflows 
 
Advanced knowledge of statistical methods for data quality assessment 
 
Experience with distributed systems and microservices architecture 
 
Background in annotation workflow optimization 
 
Track record of research publications or patents in data quality or machine learning 
 
Experience working in cross-functional teams with both technical and non-technical stakeholders 
 
Minimum Qualifications 
 
PhD in Computer Science, Machine Learning, Statistics, Math, Physics or related field, or 5 years of equivalent work experience 
 
3+ years of backend engineering experience with cloud-based services 
 
Proficiency in Python and/or Golang for backend development 
 
Experience with AWS services including Lambda and RDS/Aurora 
 
Strong foundation in applied statistics and machine learning fundamentals 
 
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. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 and $258,100, 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. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

AIML - Applied ML Engineer, Data Generation & Verification

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Unlock the Future with Amazon Science! 
 
Calling all visionary minds passionate about the transformative power of machine learning! Amazon is seeking boundary-pushing graduate student scientists who can turn revolutionary theory into awe-inspiring reality. Join our team of visionary scientists and embark on a journey to revolutionize the field by harnessing the power of cutting-edge techniques in bayesian optimization, time series, multi-armed bandits and more.
 
 
At Amazon, we don't just talk about innovation &ndash; we live and breathe it. You'll conducting research into the theory and application of deep reinforcement learning. You will work on some of the most difficult problems in the industry with some of the best product managers, scientists, and software engineers in the industry. You will propose and deploy solutions that will likely draw from a range of scientific areas such as supervised, semi-supervised and unsupervised learning, reinforcement learning, advanced statistical modeling, and graph models. 
 
Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. 
 
Join us at the forefront of applied science, where your contributions will shape the future of AI and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. 
 
Amazon has positions available for Machine Learning Applied Science Internships in, but not limited to Arlington, VA; Bellevue, WA; Boston, MA; New York, NY; Palo Alto, CA; San Diego, CA; Santa Clara, CA; Seattle, WA. 
 
Key job responsibilities 
We are particularly interested in candidates with expertise in: Optimization, Programming/Scripting Languages, Statistics, Reinforcement Learning, Causal Inference, Large Language Models, Time Series, Graph Modeling, Supervised/Unsupervised Learning, Deep Learning, Predictive Modeling
 
 
In this role, you will work alongside global experts to develop and implement novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of Reinforcement Learning and Optimization within Machine Learning. You will tackle challenging, groundbreaking research problems on production-scale data, with a focus on developing novel RL algorithms and applying them to complex, real-world challenges. 
 
The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment. 
 
A day in the life 
<ul><li>Develop scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.</li><li>Design, development and evaluation of highly innovative ML models for solving complex business problems.</li><li>Research and apply the latest ML techniques and best practices from both academia and industry.</li><li>Think about customers and how to improve the customer delivery experience.</li><li>Use and analytical techniques to create scalable solutions for business problems.
</li></ul></div><h2 class="jobSectionHeader">BASIC QUALIFICATIONS</h2><ul><li>Are enrolled in a PhD</li><li>Can relocate to where the internship is based</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with one or more of the following: Optimization, Programming/Scripting Languages, Statistics, Reinforcement Learning, Causal Inference, Large Language Models, Time Series, Graph Modeling, Supervised/Unsupervised Learning, Deep Learning, Predictive Modeling</li><li>Experience with one or more of the following: Optimization, Programming/Scripting Languages, Statistics, Reinforcement Learning, Causal Inference, Large Language Models, Time Series, Graph Modeling, Supervised/Unsupervised Learning, Deep Learning, Predictive Modeling</li><li>Must be available for full-time (40 hours per week) internship for the whole duration of the internship</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Have publications at top-tier peer-reviewed conferences or journals</li><li>Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The starting pay for this position is listed below. Final starting pay will be based on factors including experience, qualifications, and location. Starting Day 1 of employment, Amazon offers EAP, Mental Health Support, Medical Advice Line, 401(k) matching. Learn more about our benefits at https://hiring.amazon.com/why-amazon/benefits. 
USA, OR, Corvallis - 142,800.00 - 193,200.00 USD annually 
USA, WA, SEATTLE - 142,800.00 - 193,200.00 USD annually 
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually</div>

2026 Fall Applied Science Internship - Reinforcement Learning & Optimization (Machine Learning) - United States, PhD Student Science Recruiting

We&rsquo;re starting to see the incredible potential of multimodal foundation and large language models, and many applications in the computer vision and machine learning domain that previously appeared infeasible are now within reach. We are looking for a highly motivated and skilled Machine Learning Integration Engineer to join our team in the Video Computer Vision group and help us enable that potential for realtime human understanding on Apple devices. The Video Computer Vision org has pioneered human-centric real-time features such as FaceID, FaceKit, and Gaze and Hand gesture control which have changed the way millions of users interact with their devices. We balance research and product requirements to deliver Apple quality, pioneering experiences, innovating through the full stack, and partnering with HW, SW and AI teams to shape Apple's products and bring our vision to life. 
 
Description 
 
As part of the Video Computer Vision (VCV) team, you will support our ML development and continuously improve our features. Working closely with ML algorithms engineers, data scientists and quality assurance teams, you&rsquo;ll help deploy state-of-the-art computer vision technologies on Apple devices, balancing performance with the compute and power constraints of on-device inference.&quot;,&quot;responsibilities&quot;:&quot;Develop applications and tools for algorithm evaluation, prototyping, and technology demonstrations. 
 
Support teams across Apple by integrating ML and CV components into production systems. 
 
On-device integration of CV/ML algorithms. 
 
Preferred Qualifications 
 
Experience with CoreFoundation, RealityKit and CoreML. 
 
Hands-on experience with CI/CD pipelines and practices. 
 
Experience with live camera streaming applications: Understanding of real-time video pipelines, image transformations, and rendering loops. 
 
Familiarity with common computer vision techniques (e.g., object detection, segmentation, tracking, pose estimation), sequence models for real-time inference and LLMs optimized for on-device performance. 
 
Minimum Qualifications 
 
Bachelor's degree in Computer Science or related discipline, and 2 years relevant industry experience. 
 
Strong foundational knowledge in Computer Science. 
 
Extensive programming experience in Python, Swift, C++. 
 
Experience working with PyTorch. 
 
Experience with machine learning model development lifecycle, including data preprocessing, model training, evaluation, and deployment. 
 
Foundational understanding of machine learning: ML algorithms and development pipelines, with the ability to work effectively with ML practitioners and integrate ML components into production systems. 
 
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. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 and $258,100, 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. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

On-Device Machine Learning Integration Engineer

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Revolutionize the Future of AI at the Frontier of Applied Science 
 
Are you a brilliant mind seeking to push the boundaries of what's possible with artificial intelligence? Join our elite team of researchers and engineers at the forefront of applied science, where we're harnessing the latest advancements in natural language processing, deep learning, and generative AI to reshape industries and unlock new realms of innovation. 
 
As an Applied Science Intern, you'll have the unique opportunity to work alongside world-renowned experts, gaining invaluable hands-on experience with cutting-edge technologies such as large language models, transformers, and neural networks. You'll dive deep into complex challenges, fine-tuning state-of-the-art models, developing novel algorithms for named entity recognition, and exploring the vast potential of generative AI. 
 
This internship is not just about executing tasks &ndash; it's about being a driving force behind groundbreaking discoveries. You'll collaborate with cross-functional teams, leveraging your expertise in statistics, recommender systems, and question answering to tackle real-world problems and deliver impactful solutions. 
 
Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. 
 
Join us at the forefront of applied science, where your contributions will shape the future of AI and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. 
 
Amazon has positions available for LLM &amp; GenAI Applied Science Internships in, but not limited to, Bellevue, WA; Boston, MA; Cambridge, MA; New York, NY; Santa Clara, CA; Seattle, WA; Sunnyvale, CA; Pittsburgh, PA. 
 
Key job responsibilities 
We are particularly interested in candidates with expertise in: LLMs, NLP/NLU, Gen AI, Transformers, Fine-Tuning, Recommendation Systems, Deep Learning, NER, Statistics, Neural Networks, Question Answering. 
 
In this role, you will work alongside global experts to develop and implement novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of LLMs and GenAI. You will tackle challenging, groundbreaking research problems on production-scale data, with a focus on recommendation systems, question answering, deep learning and generative AI. 
 
The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment. 
 
A day in the life 
<ul><li>Collaborate with cross-functional teams to tackle complex challenges in natural language processing, computer vision, and generative AI.</li><li>Fine-tune state-of-the-art models and develop novel algorithms to push the boundaries of what's possible.</li><li>Explore the vast potential of generative AI and its applications across industries.</li><li>Attend cutting-edge research seminars and engage in thought-provoking discussions with industry luminaries.</li><li>Leverage state-of-the-art computing infrastructure and access to the latest research papers to fuel your innovation.</li><li>Present your groundbreaking work and insights to the team, fostering a culture of knowledge-sharing and continuous learning.</li></ul></div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>Are enrolled in a PhD</li><li>Can relocate to where the internship is based</li><li>Experience programming in Java, C++, Python or related language</li><li>Must be available for full-time (40 hours per week) internship for the whole duration of the internship</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Have publications at top-tier peer-reviewed conferences or journals</li><li>Experience in building models for business application</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The starting pay for this position is listed below. Final starting pay will be based on factors including experience, qualifications, and location. Starting Day 1 of employment, Amazon offers EAP, Mental Health Support, Medical Advice Line, 401(k) matching. Learn more about our benefits at https://hiring.amazon.com/why-amazon/benefits. 
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually</div>

2026 Fall Applied Science Internship - Gen AI & Large Language Models - United States, PhD Student Science Recruiting

YO IT Consulting

<div>
 
 Job Title:
 
 AI/ML Engineer
 
 
 
 Job Type:
 
 Full-Time
 
 
 
 Job Summary
 
 
 
 Join our team as a AI/ML Engineer and play a pivotal role in driving mission-critical government initiatives while also contributing to proprietary AI infrastructure, you&rsquo;ll harness advanced large language models (LLMs), retrieval-augmented generation (RAG), and multi-agent orchestration to deliver secure, scalable, and impactful machine learning systems. You&rsquo;ll work closely with cross-functional experts, leveraging frontier AI platforms and the latest in agentic AI tooling.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design, implement, and optimize AI/ML models particularly leveraging LLMs, RAG, and prompt engineering for production grade applications.
 </li>
 <li>
 Develop and orchestrate multi-agent systems using frameworks such as LangGraph and LangChain.
 </li>
 <li>
 Integrate and deploy solutions on secure cloud environments, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
 </li>
 <li>
 Build robust data pipelines, manage ETL processes, and develop metadata catalogs and ontologies to ensure high-quality data for AI training and inference.
 </li>
 <li>
 Create and maintain REST APIs and SDK integrations to facilitate seamless data and model interactions.
 </li>
 <li>
 Collaborate with product, security, and engineering teams to ensure best-in-class delivery, following secure coding and DevOps best practices (CI/CD).
 </li>
 <li>
 Document technical decisions and communicate complex concepts clearly to both technical and non-technical stakeholders.
 
 
 </li>
 </ul>
 
 Required Skills And Qualifications
 
 
 
 <ul>
 <li>
 Proficiency in Python for AI/ML development, including experience with REST APIs and SDK integration.
 </li>
 <li>
 Hands-on experience with LLMs, RAG systems, and prompt engineering in production environments.
 </li>
 <li>
 Familiarity with multi-agent orchestration, tool use, and frameworks like LangGraph and LangChain.
 </li>
 <li>
 Deep understanding of cloud AI services (AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, AWS Bedrock).
 </li>
 <li>
 Background in building and maintaining data pipelines, ontologies, metadata catalogs, and ETL processes.
 </li>
 <li>
 Strong grasp of secure coding and modern DevOps practices (CI/CD pipelines).
 </li>
 <li>
 Exceptional written and verbal communication skills for effective collaboration and documentation.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience with AI/agentic platforms, such as Anthropic for Gov, OpenAI Enterprise, Gemini Enterprise, or Grok Enterprise.
 </li>
 <li>
 Knowledge of metadata catalog platforms (MCP) and advanced API development techniques.
 </li>
 <li>
 Prior exposure to government or highly regulated cloud environments and compliance standards.
 </li>
 </ul>
</div>

AI/ML Engineer - Remote

Explore 132+ Machine learning intern in Seattle this April. Find roles across top companies and apply now to boost your career.