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software engineer

software development engineer Jobs in Seattle

software development engineer

software engineer, search data infrastructure -slack Jobs in Seattle

adversarial machine learning engineer Jobs in Seattle

adversarial machine learning engineer

ai engineer (intern)

deep learning engineer

Apple

<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

Are you passionate about Generative AI and excited to work on groundbreaking modeling technologies that will enrich the lives of billions? The Intelligence System Experience (ISE) team within Apple&rsquo;s software organization is a multidisciplinary group operating at the intersection of Multimodal Foundation Models, Efficient and Scalable ML Infrastructure, and Personalized Intelligent Experiences. As a senior machine learning engineer on our team, you will design software systems and algorithms that enable performant, scalable training and inference for Apple&rsquo;s AI-driven experiences across both on-device and server environments. This role also includes opportunities to open source your work. Join our team of highly skilled, impact-focused engineers! 
 
Description 
 
We&rsquo;re seeking strong senior machine learning engineers to help build next-generation tools for large-scale deep learning. You&rsquo;ll join a team focused on accelerating training and inference speed, improving scalability, and advancing Apple&rsquo;s centralized ML platform. Candidates should bring polished coding skills and a passion for machine learning and computational science. We offer a respectful work environment, flexible responsibilities, and access to world-class experts and growth opportunities. 
 
In this role, you will develop core components for our scalable ML platform, push the limits of existing training technologies, and create new techniques to overcome system constraints. Your work will be deployed on high-impact tasks across teams building Apple Intelligence products, with opportunities to open-source your contributions. We are especially looking for a PyTorch-focused ML efficiency expert to optimize training and inference performance, improve distributed training throughput, and drive system-level efficiency for large-scale models. If you have deep experience with PyTorch internals and high-performance ML infrastructure, we&rsquo;d love to hear from you. 
 
Preferred Qualifications 
 
Experience developing model parallel and data parallel training solutions and other training optimizations 
 
Experience with parallel training libraries such as torch.distributed, DeepSpeed, or FairScale 
 
Experience with CUDA-level optimization 
 
Experience building ML models targeting Apple Silicon 
 
Experience building large-scale deep learning infrastructure or platforms for distributed model training 
 
Publication record at Machine Learning conferences such as MLSys, NeurIPS, etc. 
 
Minimum Qualifications 
 
PhD or Master's degree in the area of Computer Science, or equivalent years of industry experience 
 
3+ years working with AI/ML technologies in production or research settings 
 
Strong Python programming skills 
 
Understanding software design principles, and algorithms 
 
Experience with deep learning frameworks, such as PyTorch 
 
Experience building large-scale distributed systems 
 
Familiarity with parallelization algorithms for large model training 
 
Familiarity with recent developments in foundation model architectures 
 
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.

Senior Machine Learning Efficiency Engineer - SIML, ISE

Are you excited about building innovative generative AI experiences that empower millions of users daily? Do you thrive in collaborative environments and enjoy applying your machine learning expertise to real-world user experiences? If so, we&rsquo;d love to hear from you. We&rsquo;re looking for a Senior Machine Learning Engineer to join the Apple Intelligence Data Platform team. This team powers key intelligence features across Apple&rsquo;s ecosystem - including Siri Suggestions, the Shortcuts app, and more - by building scalable, privacy-conscious ML systems! Our team is responsible for the Research, Development and Deployment of the core platform that powers Apple Intelligence on device and on private compute cloud - adapters, speculative decoding, guided generation to name a few. Our team is responsible for underpinning all the Apple Intelligence features we shipped to our customers including Writing Tools, Notification Summaries, ChatGPT integration, Siri and more. Our team has a great mix of talent across Machine Learning and Software Engineering. We love to share our knowledge within our team, stay abreast of state-of-the-art and deliver outstanding products for our users. We also have a strong culture of multi-functional collaboration across teams at Apple. Proactive Intelligence is central to Apple Intelligence. We&rsquo;re building a contextual, on-device platform that anticipates user needs - from predicting which app you'll launch next to understanding the difference between work and leisure modes. This is your opportunity to help shape the next generation of personal, privacy-preserving intelligence for millions of users! https://www.apple.com/apple-intelligence/ (https://www.apple.com/apple-intelligence/) 
 
Description 
 
As an engineer on the Apple Intelligence Data Platform team, you will work on developing and integrating foundational components for on-device and cloud-based intelligence. You will focus on designing, building, and deploying scalable agent systems that understand your context and personal knowledge. Your work will directly influence how users interact with Apple products through context-aware, proactive, and personalized experiences. This role is ideal for candidates with hands-on experience in Vector databases, Knowledge Graphs, Semantic Search, Retrieval-Augmented Generation (RAG), decoding strategies, Generative AI inference, and prompt optimization. You will collaborate closely with several engineering teams at Apple -such as Accessibility, Hardware, Human Interface, NLP, Privacy, etc- to power exciting Apple Intelligence features and ship them to our customers. 
 
Preferred Qualifications 
 
MS or Ph. D in Computer Science or a related field 
 
Deep understanding of machine learning and deep learning algorithms 
 
Experience in LLM, machine learning, deep learning, information retrieval or natural language processing 
 
Strong analytical and independent problem-solving skills 
 
Experience working in cross-functional teams across product, design, and infrastructure 
 
Minimum Qualifications 
 
5+ years of increasing responsibility and relevant experience 
 
Bachelor's Degree or higher in Computer Science, Artificial Intelligence, Machine Learning, Information Retrieval, Data Science or a related field. 
 
Experience in Knowledge Graphs (KG), RAG systems, integration of LLMs with external memories, Vector databases and related fields. 
 
Excellent software design, problem solving, critical thinking and collaborative skills including written and verbal communication 
 
Proficiency in one or more of the following languages: Python, Go, Java, C++, or Swift 
 
Ability to understand/clarify product requirements and translate them into technical tasks in ML modeling and engineering 
 
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.

Senior Machine Learning Engineer, Apple Intelligence Data Platform

Cerebro

<div>
 
 Are you passionate about advancing the frontier of AI? Do you thrive at the intersection of cutting-edge research and real-world impact? A fast-growing AI startup is looking for exceptional AI researchers and engineers with expertise in
 
 multimodal models
 
 to join their world-class team in
 
 Seattle, WA
 
 .
 
 
 
 About Us
 
 
 
 We are a well-funded startup backed by top-tier investors, with a mission to bring real-time AI avatars to life. Our team includes experts with advanced degrees from leading institutions and extensive experience at top tech companies. With significant funding and a clear vision, we are scaling rapidly and looking for top talent to help operationalize cutting-edge research into transformative products.
 
 
 
 What You&rsquo;ll Do
 
 
 
 As an
 
 AI Research Engineer
 
 , you&rsquo;ll play a pivotal role in bridging the gap between research and production. Your responsibilities will include:
 
 <ul>
 <li>
 
 Operationalizing Research
 
 : Collaborate with researchers to transition models from experimental checkpoints to production-ready systems. Establish scalable patterns for large-scale training, rapid experimentation, and deployment of new architectures.
 </li>
 <li>
 
 Optimizing Model Performance
 
 : Profile and enhance model inference for latency and throughput using techniques like quantization, pruning, distillation, and architectural refinements to ensure cost-effective scalability.
 </li>
 <li>
 
 Model Acceleration
 
 : Apply optimization techniques (e.g., TensorRT, ONNX, vLLM) to accelerate multimodal models, including video diffusion, large language models (LLMs), and speech models.
 </li>
 <li>
 
 Designing Data Pipelines
 
 : Build efficient pipelines for video data ingestion, preprocessing, and training at
 
 petabyte scale
 
 using tools like Dagster and Ray.
 </li>
 <li>
 
 Evaluating and Iterating
 
 : Develop evaluation frameworks to measure model quality, establish benchmarks, and guide continuous improvement of model capabilities.
 </li>
 </ul>
 
 
 What We&rsquo;re Looking For
 
 
 
 We&rsquo;re seeking candidates with a strong foundation in AI research and production engineering. The ideal candidate will have:
 
 <ul>
 <li>
 
 Production ML Experience
 
 : Proven track record of deploying ML models to production, with a deep understanding of common failure modes (e.g., resource contention, OOMs, batch optimization) and how to address them.
 </li>
 <li>
 
 Deep Learning Expertise
 
 : Strong knowledge of PyTorch and modern ML architectures, with experience training and optimizing large models (e.g., transformers, diffusion models).
 </li>
 <li>
 
 Systems Proficiency
 
 : Comfort working with GPUs, debugging CUDA issues, and profiling model workloads to identify compute or memory bottlenecks.
 </li>
 <li>
 
 Data Engineering Skills
 
 : Experience building scalable data pipelines for high-bandwidth media processing and training workflows.
 </li>
 </ul>
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Experience with
 
 video or audio models
 
 in research or production settings.
 </li>
 <li>
 Familiarity with
 
 low-level optimization
 
 (e.g., CUDA kernels, Triton, custom operators).
 </li>
 <li>
 Knowledge of
 
 real-time ML systems
 
 and latency-critical inference.
 </li>
 <li>
 Prior work with
 
 model compression techniques
 
 (quantization, distillation, pruning).
 </li>
 </ul>
 
 
 Why Join Us?
 
 
 <ul>
 <li>
 
 Impactful Work
 
 : Your contributions will directly shape the future of real-time AI avatars, advancing cutting-edge research into products that touch millions of lives.
 </li>
 <li>
 
 World-Class Team
 
 : Collaborate with some of the brightest minds in AI, including researchers and engineers from top institutions and companies.
 </li>
 <li>
 
 Growth Opportunities
 
 : Be part of a fast-growing startup with significant funding and a clear vision for the future.
 </li>
 <li>
 
 In-Person Collaboration
 
 : Work alongside your teammates in our vibrant
 
 Seattle HQ
 
 , fostering creativity and innovation through daily collaboration.
 </li>
 </ul>
 
 
 How to Apply
 
 
 
 If you&rsquo;re excited about the opportunity to work on
 
 multimodal AI models
 
 and help bring groundbreaking research to life, we&rsquo;d love to hear from you! Apply now to join a team shaping the future of AI.
 
</div>

Artificial Intelligence Researcher

MORSE Corp

<div>
 
 MORSE Corp is an employee owned, small business based in Cambridge, MA, Arlington, VA, and Seattle, WA with a history of fielding
 
 cutting-edge
 
 
 technology. MORSE boasts a specially selected team of scientists, engineers, and software developers to deliver best-in-class technical solutions that solve difficult multidisciplinary problems faced by the US National Security Ecosystem.
 
 
 &nbsp;
 
 
 
 
 We are seeking a Machine Learning Engineer to join our team at MORSE.  You will play a pivotal role in designing, implementing, and managing complex ML algorithms and systems, with a focus on computer vision (CV) and other types of data. You will be responsible for acquiring truth data, integrating algorithms, testing algorithms, combining algorithms, reviewing literature to stay on top of the latest-and-greatest methods, analyzing data from field tests, and developing advanced algorithms.  MORSE&rsquo;s AI &amp; ML work crosses modalities, and experience or interest in the fields of Large Language Models (LLM), audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE&rsquo;s current team of engineers to transition algorithms to production, which may run on on-prem servers, on the cloud, or on a real-time embedded system. You will be part of our team working to accelerate our US National Security customers abilities to use natural language processing capabilities in mission-critical environments.
 
 
 &nbsp;
 
 
 
 Responsibilities:
 
 
 &nbsp;
 
 <ul>
 <li>
 
 Develop, fine-tune, train, and optimize Computer Vision algorithms processing tasks such as object detection and tracking.&nbsp;
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Use MLOps tools for efficient experiment tracking, data management, and reproducibility
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Write robust, efficient, and maintainable code
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Track the latest advancements with machine learning research to bring new techniques and methodologies to MORSE
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Conduct experiments and perform rigorous evaluations to assess the effectiveness and efficiency of CV models
 
 
 &nbsp;
 
 
 </li>
 </ul>
 
 Skills and Requirements:
 
 
 &nbsp;
 
 <ul>
 <li>
 
 US CITIZENSHIP REQUIRED and the ability to obtain a U.S. Security Clearance
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Masters or Ph.D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or related field
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Proven experience in applying CV models, techniques, frameworks, and libraries to implement and fine-tune models
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Proven experience testing and validating the performance of AI technologies in real-world applications
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Proficiency in Python
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience with cloud platforms (AWS and Azure)
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience with Docker
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience with MLOps tools such as Airflow, MLFlow, AimStack, etc.
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Exceptional communication skills and the ability to work well with customers
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Understanding of Department of Defense requirements and standards is a plus
 
 
 &nbsp;
 
 </li>
 </ul>
 
 
 &nbsp;
 
 
 
 
 
 
 &nbsp;
 
 
 
 
 &nbsp;
 
 
 
 MORSE Corp&rsquo;s salary range for this role carefully considers a wide range of compensation factors, including but not limited to, prior experience, education, skills and expertise, location, internal equity, and other factors that are job related and consistent with business need. Therefore, final offer amounts may vary from the amount stated. Depending on role eligibility, total compensation may also include bonus, stock, 401(k) match, paid time off, medical, dental, vision and life insurance.Employees also receive 10 paid holidays per year. MORSE maintains an &ldquo;open&rdquo; leave policy that does not restrict exempt, regular full-time employees to a specific&nbsp;number of paid sick or vacation days. However, this policy is not an &ldquo;unlimited&rdquo; paid leave policy.&nbsp;
 
 
 Compensation: $90,000 USD - $210,000 USD
 
 
 The team at MORSE takes pride in being the smart team that is easy to work with. We focus on steady, long-term success while maintaining a collaborative, enjoyable work experience for our employees. Our team values work-life balance through flexibility and other programs, along with a comprehensive benefits package for employees and families. For more information, please visit www.morsecorp.com.
 
 
 
 &nbsp;
 
 
</div>

Machine Learning Engineer

The Applied Machine Learning team builds production multimodal systems that understand and transform large-scale image, audio, and video content. Our work spans diffusion-based image generation, transcription and diarization, face and object detection, OCR and image description for search, and automated quality control of media pipelines. 
 
We are looking for a Staff Machine Learning Engineer to strengthen our diffusion and video models, adapt small and mid-sized LLMs, and turn our uniquely large corpus of weakly labeled media into a durable product advantage. This is an opportunity to shape the next generation of multimodal experiences end-to-end, from data and models to evaluation and user impact. 
 
Description 
 
The Staff Machine Learning Engineer - Multimodal Generation &amp; Post-Training will be a senior individual contributor on a small, applied ML team focused on production multimodal systems. The role will lead fine-tuning and adaptation of diffusion and emerging video models, as well as post-training of small and medium LLMs for captioning, moderation, and retrieval-friendly descriptions. 
 
The engineer will design data and evaluation workflows that use our large archive of weakly labeled music, podcast, film, TV, and short-form content to drive measurable quality and efficiency improvements. The role includes close collaboration with partner infra teams for model serving and with adjacent product and research groups to bring new capabilities into production. 
 
Preferred Qualifications 
 
PhD in Computer Science, Machine Learning, or a related technical field. 
 
8+ years of industry experience with production multimodal systems spanning image, audio, and/or video. 
 
Deep expertise with diffusion and video generation techniques (e.g., ControlNet/IP-Adapter, temporal consistency methods, sampling and latency optimization). 
 
Experience with PEFT/QLoRA and post-training approaches such as DPO or related preference-based methods for small and mid-sized LLMs. 
 
Background in ASR/VAD/diarization, OCR, multimodal retrieval, or face recognition with fine-grained temporal alignment. 
 
Familiarity collaborating with infra/platform teams on model serving (e.g., batching strategies, quantization, observability) and translating requirements into reliable production deployments. 
 
Demonstrated ability to define metrics, build evaluation harnesses, and communicate results clearly to cross-functional partners. 
 
Track record of publications, patents, or open-source contributions in relevant areas of machine learning or multimodal modeling. 
 
Minimum Qualifications 
 
Master&rsquo;s degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience. 
 
5+ years of hands-on industry experience building and shipping machine learning systems to production. 
 
Proven experience training and fine-tuning diffusion or other image/video generative models, including adapter-based methods such as LoRA. 
 
Proficiency in Python and at least one major deep learning framework such as PyTorch. 
 
Experience designing and operating ML pipelines for noisy or weakly labeled data, including offline evaluation and monitoring in production. 
 
Strong software engineering skills, including code quality, experimentation discipline, and debugging/profiling of model performance. 
 
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 $201,300 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.

Staff Machine Learning Engineer, 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
 
 
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AI Engineer (Intern)

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