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aiml - applied ml engineer, data generation & verification Jobs in Seattle

nlp engineer

Apple

From our origins in iPhone keyboard input, the Input Experience NLP team has expanded to a broad charter: improve the user experience with robust language understanding and personalized text composition, across languages and Apple platforms. We build the ML models that underlie Summarization, Smart Reply, Writing Tools, and other features deeply integrated into Apple products. Generative AI is a transformative technology that we have only just begun to incorporate into our digital lives, to help everyday people digest the deluge of information they receive and express themselves more clearly. On our team, you will help build the future and have a voice in the shape it takes. 
 
We are looking for a Machine Learning Engineer to develop the next generation of our ML models, so that they better serve the full range of our customers, across languages, writing styles, and other personal context, in a privacy-preserving way. You will build, run, and refine the training and evaluation pipelines that define our slice of Apple Intelligence, driving the focused experimentation and iteration that makes the user experience magical. You will join an ambitious, organized, and collaborative team. We&rsquo;re in a unique position to integrate the latest innovations from the ML community and work on features that reach everyday users, including your family and friends. You&rsquo;ll work closely with teams across Apple, collaborating on human interfaces, user studies, internationalization, ML technologies, system integration, and more. 
 
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. 
 
Description 
 
As a Machine Learning Engineer on our team, you will enable next-generation AI applications by building toolkits and workflows that scale to increasingly sophisticated modeling tasks. You will design the abstractions and implement the algorithms that facilitate efficient data synthesis, data curation, prompt engineering, and model evaluation. You will contribute to a company-wide effort to build robust modeling pipelines that optimize our ability to iterate rapidly and continuously deliver improvements to our customers. Finally, you will help define and refine new features that expand both the depth of Apple Intelligence&rsquo;s capabilities and the breadth of its support for the full spectrum of Apple customers&quot;,&quot;responsibilities&quot;:&quot;Development and maintenance of data and model pipelines that scale to deployment in production 
 
Building toolkits for iterating on model quality via data synthesis and prompt engineering 
 
Definition of robust automated evaluation mechanisms to facilitate hillclimbing on model quality 
 
Failure analysis from user feedback to understand shortcomings of our models and evaluation data 
 
Research into state-of-the-art techniques for improving model quality and robustness 
 
Implementation of experiments and simulations to assess the value of model changes 
 
Preferred Qualifications 
 
Familiarity with LLMs, such as SFT, RHLF, prompt engineering, data synthesis, automatic evaluation, and RAG 
 
Expertise in MLOps and a passion for software quality, based on CI/CD principles 
 
Excellent written and verbal communication skills 
 
Background in linguistics, fluency in multiple languages, or a passion for scaling NLP features for global audiences 
 
History of developing Python packages and supporting users and other teams 
 
Minimum Qualifications 
 
MS or PhD in Computer Science or related field with at least 2 years of industry experience 
 
Strong Python programming skills, with experience developing production-quality Python modules 
 
Experience building and maintaining model pipelines end-to-end, from data curation to evaluation 
 
Solid background in machine learning, data science, natural language processing, or statistics 
 
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, Natural Language Generation

Unify Consulting

<div><div><div>At Unify, we help organizations turn AI ambition into real-world impact. As an AI-focused management consulting firm, we partner with leading enterprises to design, build, and scale intelligent systems that transform how work gets done. From strategy through execution, our teams operate at the intersection of advanced machine learning, cloud-native architecture, and business outcomes&mdash;bringing Generative AI out of experimentation and into production.</div> 
<div></div>
<div></div>
<div>Location Requirement 
This is a full-time, 5-day onsite role based in Seattle, WA. Candidates must currently live in the Seattle area or be willing to go onsite for interview and be able to relocate prior to start. Remote or hybrid arrangements are not available for this position.</div>
</div><h3 class="jobSectionHeader">The Role</h3>
Unify is seeking an experienced Data Scientist / Applied Scientist to help design and deliver cutting-edge, production-grade AI solutions for our clients. This role is ideal for someone who thrives in complex problem spaces and enjoys translating advanced machine learning techniques into scalable, business-ready applications. This position requires a full-time, 5-day onsite presence in Seattle, enabling close collaboration with client stakeholders and cross-functional delivery teams.

You will work hands-on with Large Language Models (LLMs) and modern NLP techniques, leveraging AWS services such as Amazon Bedrock to build intelligent systems that enhance customer experience and unlock new value. The work spans model development, system design, and active participation in client-facing engagements&mdash;ensuring solutions are not only technically robust, but also practical, trusted, and impactful in real-world environments.<div> 
</div><h3 class="jobSectionHeader">
Key Responsibilities</h3><ul>
<li><div>Design, develop, and deploy advanced machine learning and deep learning models to solve complex business problems</div>
</li><li><div>Build and optimize large-scale NLP and Generative AI solutions, including applications leveraging LLMs</div>
</li><li><div>Develop scalable data pipelines and AI architectures to support production-grade deployments</div>
</li><li><div>Implement and support Retrieval-Augmented Generation (RAG) patterns to improve accuracy, relevance, and grounding of model outputs</div>
</li><li><div>Collaborate closely with consulting, engineering, and client teams to support data-driven decision-making</div>
</li><li><div>Contribute to best practices across model development, deployment, and MLOps</div>
</li></ul><h3 class="jobSectionHeader">Requirements</h3><ul>
<li>Master&rsquo;s degree in Computer Science, Machine Learning, or a related field</li>
<li>5+ years of experience in applied machine learning and deep learning</li>
<li>Strong proficiency in Python and modern ML frameworks</li>
<li>Extensive hands-on experience with Large Language Models and transformer-based architectures</li>
<li>Demonstrated experience deploying ML models into production environments</li>
<li>Strong experience with AWS, including Amazon Bedrock, SageMaker, Lambda, ECS, and S3</li>
<li>Familiarity with MLOps practices, tooling, and model lifecycle management</li>
<li>Hands-on experience designing and implementing RAG architectures</li>
</ul>
Preferred Experience:
<ul>
<li>Knowledge of vector databases and semantic search</li>
<li>Experience with prompt engineering and model fine-tuning</li>
<li>Familiarity with containerization and microservices architectures</li>
<li>Ability to clearly communicate technical concepts to non-technical stakeholders</li>
</ul><h3 class="jobSectionHeader">Please Note</h3><div>
<ul><li>We are unable to sponsor or transfer visas for this position. You must be authorized to work in the United States for any employer without requiring sponsorship or visa transfer now or in the future.</li>
<li>You must currently live in the Greater Seattle area, and be willing to go onsite 5 days/week</li>
<li>Please no resumes from third-party agencies or recruiters</li></ul></div></div><div></div>

Data Scientist/Applied Scientist - Onsite in Seattle

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

<div>
 
 Summary
 
 
 
 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'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.
 
 
 Your work may span a variety of directions, including but not limited to:
 
 
 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.
 
 
 
 Minimum Qualifications
 
 
 
 <ul>
 <li>
 Demonstrated expertise in computer vision, natural language processing, and machine learning with a passion for data-centric machine learning.
 </li>
 <li>
 Deep understanding in multi-modal foundation models.
 </li>
 <li>
 Staying on top of emerging trends in generative AI and multi-modal LLM.
 </li>
 <li>
 Strong programming skills and hands-on experience using the following languages or deep learning frameworks: Python, PyTorch, or Jax.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 3+ years of experience with developing and evaluating ML applications, and demonstrated experience in understanding and improving data quality.
 </li>
 <li>
 Strong publication record in relevant conferences (e.g. CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, , etc)
 </li>
 <li>
 Strong problem-solving and communication skills.
 </li>
 <li>
 Ph.D/MS degree in Machine Learning, Natural Language Processing, Computer Vision, Data Science, Statistics or related areas
 
 
 </li>
 </ul>
 
 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 $147,400 and $272,100, 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&rsquo;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&rsquo;s Employee Stock Purchase Plan. You&rsquo;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 &mdash; 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.
 
 
 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.
 
 
 Apple accepts applications to this posting on an ongoing basis.
 
 
</div>

AIML - Machine Learning Engineer, Data and ML Innovation

At Apple, we believe that technology should enrich people's lives in meaningful ways. Apple Services-including the App Store, Apple Music, Apple TV+, and Podcasts-connect millions of users worldwide to the content and experiences they love. Behind these services are sophisticated AI and machine learning systems that power personalized recommendations, intelligent search, and content discovery. The quality of these experiences depends fundamentally on the integrity of the data that fuels them. 
 
Join the Human-centered AI (HAI) organization within Apple Services Engineering as a Senior Applied Scientist on our Data Quality Operations team. This is your opportunity to shape the future of data quality at Apple, working at the intersection of cutting-edge machine learning, large language models, and rigorous scientific methodology. You'll be at the forefront of designing and implementing novel, scalable quality control solutions which ensure our AI-powered services meet Apple's exacting standards for a high-quality user experience. If you're passionate about applying scientific rigor to real-world problems, thrive on innovation, and want your work to impact hundreds of millions of users, this role offers an exceptional opportunity to make a lasting contribution to products people use every day. 
 
Description 
 
We are seeking a Senior Applied Scientist to lead the design and implementation of novel, scalable quality control solutions for Apple Services. In this role, you will develop AI or ML solutions for programatically generating gold standard datasets, create anomaly detection systems, and pioneer use of Large Language Models for automated quality control. You will work closely with cross-functional teams to ensure the data powering our AI/ML systems meets the highest standards of accuracy, consistency, and relevance. 
 
&quot;,&quot;responsibilities&quot;:&quot;Develop methodologies and systems to programatically generating gold standard datasets to measure and improve data quality across diverse content types. 
 
Build and validate LLM-based grading systems that align with human judgment for tasks including content classification, quality assessment, and metadata validation. 
 
Create and deploy anomaly detection systems to proactively identify data inconsistencies, biases, and errors across production pipelines. 
 
Collaborate with AI/ML engineering, product, and data science teams to identify quality challenges and integrate solutions into production workflows. 
 
Stay abreast of the latest advancements in machine learning, AI, data quality, and LLM research, applying relevant techniques to enhance our capabilities. 
 
Mentor and guide junior team members, fostering technical excellence and innovation in data quality operations. 
 
Communicate findings and recommendations clearly to technical and non-technical stakeholders, including senior leadership. 
 
Preferred Qualifications 
 
PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, NLP or a related quantitative field with 3+ years of relevant industry experience, 
 
Experience with data labeling operations, annotation quality frameworks, or human-in-the-loop systems. 
 
Familiarity with prompt optimization frameworks or automated prompt engineering. 
 
Experience in natural language processing (NLP) or natural language understanding (NLU). 
 
Experience with MLOps practices and tools for deploying, monitoring, and managing ML models in production. 
 
Familiarity with cloud platforms (e.g., AWS, GCP, Azure) or large-scale distributed infrastructure systems. 
 
Prior experience contributing to open-source projects or publishing research in relevant academic conferences or journals. 
 
Minimum Qualifications 
 
3+ years of industry experience in an Applied Scientist, Machine Learning Engineer, or Data Scientist role with focus on data quality, evaluation, or related areas. 
 
Proven experience designing, building, and deploying scalable data quality or evaluation systems in production environments. 
 
Strong hands-on experience with Large Language Models (LLMs) including prompt engineering, fine-tuning, and applications such as grading, validation, or classification. 
 
Proficiency in Python, data science libraries (pandas, NumPy, scikit-learn, PyTorch, TensorFlow), SQL, and distributed computing environments (Spark, Hadoop). 
 
MS in Computer Science, Machine Learning, Statistics, Applied Mathematics, NLP or a related quantitative field with 3+ years of relevant industry experience, OR BS degree in a related quantitative field with 8+ years of relevant industry experience. 
 
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 $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.

Sr Applied Scientist, AI/ML Evaluation Quality, Apple Services Engineering

Juniper Square

<div>
 
 About Juniper Square
 
 
 
 Our mission is to unlock the full potential of private markets. Privately owned assets like commercial real estate, private equity, and venture capital make up half of our financial ecosystem yet remain inaccessible to most people. We are digitizing these markets, and as a result, bringing efficiency, transparency, and access to one of the most productive corners of our financial ecosystem. If you care about making the world a better place by making markets work better through technology &ndash; all while contributing as a member of a values-driven organization &ndash; we want to hear from you.
 
 
 Juniper Square offers employees a variety of ways to work, ranging from a fully remote experience to working full-time in one of our physical offices. We invest heavily in digital-first operations, allowing our teams to collaborate effectively across 27 U.S. states, 2 Canadian Provinces, India, Luxembourg, and England. We also have physical offices in San Francisco, New York City, Mumbai and Bangalore for employees who prefer to work in an office some or all of the time.
 
 
 
 About Your Role
 
 
 
 We're looking for an AI Engineer Intern to join our team who is excited to help transform the private markets. In this role, you&rsquo;ll work alongside a talented and collaborative team focused on one of our top strategic initiatives - bringing cutting-edge AI innovation to a key product feature that will drive real change in the industry.
 
 
 As an intern, you&rsquo;ll have a hands-on role in designing, building, and testing new AI-driven product features. This isn&rsquo;t a side project - it's a core company priority with executive visibility and high impact. You&rsquo;ll work in close partnership with engineers, product leaders, and mentors who are invested in your growth and success.
 
 
 You&rsquo;ll also gain valuable exposure to company leadership, access to world-class mentorship, and the opportunity to contribute meaningfully to a product that&rsquo;s reshaping how the private markets operate. For the right person, this internship can be a launchpad into a full-time role post-graduation.
 
 
 This opportunity is perfect for someone with a strong engineering foundation who is currently pursuing a master&rsquo;s degree in AI or a related field - and who&rsquo;s excited to innovate, learn fast, and make a real-world impact.
 
 
 
 This is a remote role based in the U.S. or Canada. The internship program runs for 11 weeks at 40 hours per week, with a scheduled start date of Monday, June 8th.
 
 
 
 
 There may be an opportunity to travel to our San Francisco office the final week to participate in the annual Hackathon.
 
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Collaborate with engineers and product managers to design and prototype AI-powered features that directly impact a key product area at the core of our business
 </li>
 <li>
 Contribute to the development, training, and evaluation of machine learning and natural language processing (NLP) models using industry-standard tools and frameworks
 </li>
 <li>
 Work with large and complex datasets - performing data preprocessing, feature engineering, and analysis to support model development
 </li>
 <li>
 Apply foundational machine learning and deep learning techniques to solve real-world problems in the private markets space
 </li>
 <li>
 Assist with integrating AI models into production systems, including testing, validation, and iteration in collaboration with the engineering team
 </li>
 <li>
 Support ongoing research and experimentation efforts, particularly around NLP and large language models (LLMs), to drive innovation in product development
 </li>
 <li>
 Partner closely with engineering, design, and product stakeholders to evaluate the technical feasibility and ensure alignment of proposed AI features with the overall product vision and strategy.
 </li>
 <li>
 Participate in regular team meetings, code reviews, and brainstorming sessions - bringing curiosity, ideas, and technical insight to the table
 </li>
 <li>
 Receive mentorship from experienced AI and engineering leaders, while gaining exposure to company leadership and strategic initiatives
 </li>
 <li>
 Contribute to documentation and knowledge sharing to help scale AI development efforts across the team
 </li>
 <li>
 Take ownership of meaningful projects with the potential to influence long-term company strategy and product direction
 </li>
 <li>
 Embrace a growth mindset - continuously learning new tools, methodologies, and concepts in the rapidly evolving field of AI
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 Education &amp; Academic Background
 
 
 
 <ul>
 <li>
 Currently pursuing a Master&rsquo;s degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, or a related quantitative field (e.g., Mathematics, Statistics, Physics)
 </li>
 <li>
 Strong academic foundation with relevant coursework in algorithms, data structures, linear algebra, calculus, probability, and statistics
 </li>
 <li>
 Completed or currently enrolled in courses in machine learning, deep learning, NLP, or computer vision (highly desirable)
 
 
 </li>
 </ul>
 
 Technical Skills
 
 
 
 <ul>
 <li>
 Proficient in Python; experience with libraries such as TensorFlow, PyTorch, scikit-learn, NumPy, and Pandas is a plus
 </li>
 <li>
 Familiarity with data manipulation, preprocessing, and feature engineering techniques
 </li>
 <li>
 Exposure to databases (SQL/NoSQL) and data querying; experience with data visualization tools (e.g., Looker, Tableau, Power BI) is a bonus
 </li>
 <li>
 Understanding of foundational ML algorithms (e.g., regression, decision trees, clustering) and the underlying mathematical concepts
 </li>
 <li>
 A strong grasp of Large Language Model (LLM) mechanisms, including knowledge of sampling strategies, structured output generation, and function-calling capabilities. Hands-on experience with prompt engineering is a strong plus
 </li>
 <li>
 Exposure to cloud platforms (e.g., AWS, GCP) and cloud-based ML services (e.g., Amazon SageMaker, Google AI Platform) is beneficial
 </li>
 <li>
 Basic knowledge of software engineering practices, including version control (Git), Agile development, and API integration (REST, GraphQL)
 
 
 </li>
 </ul>
 
 Soft Skills &amp; Mindset
 
 
 
 <ul>
 <li>
 Strong analytical and problem-solving skills with a high attention to detail
 </li>
 <li>
 Eagerness to learn and apply new AI concepts in a fast-paced, evolving environment
 </li>
 <li>
 Clear and effective communication skills, both written and verbal
 </li>
 <li>
 Collaborative mindset with the ability to contribute meaningfully to team discussions and technical problem-solving
 </li>
 <li>
 Self-starter with curiosity, initiative, and a proactive approach to innovation
 
 
 </li>
 </ul>
 
 Bonus Points
 
 
 
 <ul>
 <li>
 Personal AI/ML projects (e.g., GitHub portfolio)
 </li>
 <li>
 Participation in AI/ML competitions or hackathons
 </li>
 <li>
 Research experience or academic publications in AI-related areas
 </li>
 <li>
 Contributions to open-source projects
 
 
 </li>
 </ul>
 
 Compensation
 
 
 
 Compensation for this position includes an hourly rate. The U.S. hourly rate is $50.00 USD and the Canadian hourly rate is $57.00 CAD.
 
 
 #Juniper-US
 
 
 #Juniper-Canada
 
 
 #emergingtalent
 
 
</div>

AI Engineer (Intern)

The Apple Knowledge Quality Team is building the next-generation of machine learning solutions for Knowledge Q&amp;A at Apple and help power features including Siri and Spotlight. The features we build are redefining how hundreds of millions of people use their computers and mobile devices to search and find what they are looking for. As part of this group, you will work with one of the most exciting high performance computing environments, with petabytes of data, millions of queries per second, and have an opportunity to imagine and build products that delight our customers every single day. 
 
Description 
 
The Knowledge Quality team is looking for extraordinary Machine Learning engineers to join a team of world-experts on Large-Scale Data Management and Machine Learning Systems. Together, you will be pushing the boundaries of Knowledge Question Answering in Siri. As part of the Knowledge Quality team, you will design and develop features for a platform that touches upon large-scale data management, machine-learning and deep learning systems over graph data and web documents. You will have the outstanding opportunity to inform product evolution through measurement, evaluation, and analysis of the user experience. You will partner with cross-functional teams to change how hundreds of millions of people use their computers and mobile devices to search and provide users with results that best satisfy their information seeking needs. 
 
Preferred Qualifications 
 
MS degree with 6+ years of industry experience building and scaling ML/AI systems, OR PhD degree with 3+ years of industry experience in production ML environments 
 
Proven track record designing, deploying, and maintaining large-scale distributed ML systems serving millions of QPS (queries per second) 
 
Experience with A/B testing, experimentation frameworks, and data-driven product iteration at scale 
 
Experience designing human-in-the-loop evaluation pipelines and leveraging user feedback to improve model performance 
 
Hands-on experience with LLM deployment, prompt engineering, fine-tuning, RAG (Retrieval-Augmented Generation), or other generative AI technologies in production 
 
Experience building model monitoring, observability, and quality assurance systems for production ML services 
 
Experience optimizing ML systems for latency, throughput, and cost at scale 
 
Track record of shipping ML-powered features that measurably improved user experience for consumer-facing products 
 
Strong product intuition and ability to translate business requirements into technical solutions 
 
Minimum Qualifications 
 
MS degree in Computer Science, Machine Learning, or related field with 2+ years of industry experience building production ML/AI systems, OR PhD degree in a related field 
 
Proficiency in mainstream programming languages such as Python, Scala, and Go 
 
Experience building and maintaining large-scale data systems, knowledge graphs, and end-to-end ML pipelines in production, ideally using the Apache software stack (e.g., Spark) 
 
Hands-on experience with machine learning frameworks such as PyTorch or TensorFlow in production environments 
 
Experience with natural language processing, statistical data analysis, and model evaluation methodologies 
 
Demonstrated ability to collaborate with cross-functional teams including product, engineering, and data science 
 
Experience with CI/CD pipelines, model deployment, and monitoring solutions 
 
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 Search & Knowledge Platforms

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