aiml - applied ml engineer, data generation & verification

aiml - sr backend engineer, data and ml innovation

aiml - sr machine learning engineer, data and ml innovation

applied scientist, prime video - content localization, understanding & enrichment

patient transporter (full time and part time)

ai / software engineering intern Jobs in Seattle

ai / software engineering intern

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

aiml - sr backend engineer, data and ml innovation Jobs in Seattle

aiml - sr machine learning engineer, data and ml innovation Jobs in Seattle

applied scientist, prime video - content localization, understanding & enrichment Jobs in Seattle

aiml sr machine learning engineer data and ml innovation

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

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

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

Uber

<div>About the Role
 
 
Uber's Marketplace is at the core of the business. The Earner Incentive team in Marketplace builds products and systems that empower drivers through targeted incentives, creating a more balanced and efficient marketplace while enhancing engagement and experience.
 
 
The team owns the end-to-end incentive lifecycle, from ML-driven incentive generation to scalable online serving, answering questions such as who, where, when, how, and how much, powered by large-scale machine learning, optimization, and experimentation systems . These systems enable proactive, targeted incentives that shape supply, optimize earnings, and guide marketplace balance.
 
 
We are seeking a Senior Machine Learning Engineer to design and scale the technical foundations behind Uber's driver incentive systems. You will develop and productionize large-scale ML models and decision systems that power both scheduled and near real-time, intelligent incentive generation and delivery at Uber's global scale.
 
 
In this role, you will collaborate closely with engineers, product managers, operations, and scientists to set technical direction, make thoughtful trade-offs, and turn complex problems into reliable production systems. Your work will directly shape how incentives are designed and delivered at scale, enhancing marketplace efficiency and reliability, and empowering earning opportunities for millions of drivers worldwide.
 
 
What the Candidate Will Do
<ul><li>Design, develop, productionize, and operate end-to-end ML solutions and data pipelines for large-scale systems that power driver incentives.
</li><li>Develop and apply advanced ML and optimization techniques to design incentive mechanisms for online marketplaces, improving marketplace efficiency and reliability while enabling earning opportunities for millions of drivers.
</li><li>Build deep domain expertise in incentives, pricing, and marketplace dynamics, and understand how these systems interact with Operations. Translate business requirements into clear problem statements and actionable technical plans, reasoning through trade-offs to deliver practical, production-ready solutions.
</li><li>Help set the team's technical direction and drive execution in partnership with technical leads. Provide technical mentorship, and review designs and code to maintain high engineering quality.
</li><li>Collaborate closely with engineers, product managers, scientists, and Operations to drive clarity, alignment, and delivery of high-impact solutions to complex business problems.
</li><li>Own projects end-to-end, from ideation and design through production rollout and iteration, and drive measurable business impact across teams.
</li></ul>Basic Qualifications
<ul><li>Ph.D., M.S., or Bachelor's degree in Computer Science, Statistics, Mathematics, Machine Learning, Operations Research, or a related field, or equivalent practical experience with demonstrated impact.
</li><li>5+ years of experience across the end-to-end ML lifecycle, including data analysis, feature engineering, model development, deployment, monitoring, and iteration in large-scale production systems. Proven ability to deliver measurable business impact and strong understanding of MLOps best practices.
</li><li>Strong understanding of a broad range of ML and statistical techniques, including deep learning (e.g., multi-task learning, transformers), tree-based models, and classical approaches, with solid judgment in selecting methods based on context and data.
</li><li>Proficiency in at least one production language (Python, Scala, Java, or Go) and common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
</li><li>Solid software engineering skills, including system design, writing and reviewing production-quality code, testing, and operating ML systems in production.
</li><li>Strong ownership, learning mindset, collaboration and communication skills; able to work independently and effectively in cross-functional teams.
</li></ul>Preferred Qualifications
<ul><li>Experience developing and deploying pricing, matching, or incentive algorithms for two-sided marketplaces, with strong product intuition and system-level thinking.
</li><li>Experience with multi-armed bandits, reinforcement learning, and causal ML, including applying these methods in production systems.
</li><li>Familiarity with large-scale data and ML infrastructure (e.g. Spark, Flink), and batch or real-time data processing systems.
</li><li>Strong communication and leadership skills, with the ability to lead initiatives, prototype quickly, drive alignment, and collaborate effectively with cross-functional partners, from early idea generation through productionization.
</li><li>Experience leading complex technical projects, influencing scope, technical direction, and execution across multiple engineers or teams.
</li><li>Ability to translate ambiguous business problems into clear, actionable problem statements, define success metrics, and drive execution through well-reasoned trade-offs.
</li><li>Demonstrated technical leadership, such as mentoring engineers, leading cross-functional efforts, or shaping ML / optimization strategy.
</li>Experience designing, running and analyzing large-scale online experiments to prove impact, interpret results, guide decision-making, and translate insights into concrete product or system changes. 
<li>
</li></ul> 
 
For San Francisco, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.</div>

Senior Machine Learning Engineer - Earner Incentive

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intelligence (AI) systems? Want to help the largest global enterprises derive business value through the adoption and automation of Generative AI (GenAI)? Excited by using massive amounts of disparate data to develop AI/ML models? Eager to learn to apply AI/ML to a diverse array of enterprise use? Thrilled to be a key part of Amazon, who has been investing in Machine Learning for decades - pioneering and shaping the world&rsquo;s AI technology? 
 
The Amazon Web Services Professional Services (ProServe) team is seeking a skilled ML Engineer to join our team as a Delivery Consultant at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS AI/ML and GenAI solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the ML project lifecycle. You will lead customer-focused project teams as a technical leader, and perform hands-on development of ML solutions with exceptional quality 
 
Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure AI/ML and GenAI solutions tailored to meet the specific needs of each customer. You&rsquo;ll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project. 
 
The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries. 
 
Key job responsibilities 
Key job responsibilities 
As an experienced technology professional, you will be responsible for: 
1. Leading project teams and implementing end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment and monitoring 
2. Designing and implementing machine learning pipelines that support high-performance, reliable, scalable, and secure ML workloads 
3. Designing scalable ML solutions and operations (MLOps) using AWS services and leveraging GenAI solutions when applicable 
4. Collaborating with cross-functional teams (Applied Science, DevOps, Data Engineering, Cloud Infrastructure, Applications) to prepare, analyze, and operationalize data and AI/ML models 
5. Serving as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures 
6. Sharing knowledge and best practices within the organization through mentoring, training, publication, and creating reusable artifacts 
7. Ensuring solutions meet industry standards and supporting customers in advancing their AI/ML, GenAI, and cloud adoption strategies 
 
This is a customer-facing role with potential travel to customer sites as needed. 
 
About the team 
Diverse Experiences
 
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn&rsquo;t followed a traditional path, or includes alternative experiences, don&rsquo;t let it stop you from applying.
 
 
Why AWS
 
Amazon Web Services (AWS) is the world&rsquo;s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating &mdash; that&rsquo;s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. 
 
Work/Life Balance
 
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve in the cloud. 
 
Inclusive Team Culture
 
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 
 
Mentorship and Career Growth 
We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.<h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>Bachelor's degree in Computer Science, Engineering, a related field, or equivalent experience</li><li>5+ years of cloud architecture and solution implementation experience</li><li>5+ years of development/programming/scripting language (Python/Java/Bash/Perl) experience</li><li>5+ years leading technical teams and hands-on experience focused on data, software, or ML engineering, with understanding of distributed computing (e.g., data pipelines, training and inference, ML infrastructure design)</li><li>5+ years developing predictive modeling, natural language processing, and deep learning, with experience in building and deploying ML models on cloud (e.g., Amazon SageMaker or similar)</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience with the AWS platform, web services, software development, or related technologie</li><li>Experience conveying complex technical concepts to both technical and business audiences</li><li>Knowledge of one or more ML Frameworks (e.g., PyTorch, TensorFlow) and ML methods including NLP models (BERT, GPT-2/3), computer vision-based models (object detection, image recognition), and text-based models (Seq2Seq, Topic modeling)</li><li>Experience with automation (e.g., Terraform, Python), Infrastructure as Code (e.g., CloudFormation, CDK), and Containers &amp; CI/CD Pipelines</li><li>Knowledge of common security and compliance standards (e.g., HIPAA, GDPR)</li><li>Experience building ML pipelines with MLOps best practices, including: data preprocessing, model hosting, feature selection, hyperparameter tuning, distributed &amp; GPU training, deployment, monitoring, and retraining</li><li>Experience with MLOps (e.g., MLFlow, Kubeflow) and orchestration (e.g., Airflow, AWS Step Functions). Experience building applications using GenAI technologies (LLMs, Vector Stores, LangChain, Prompt Engineering)</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. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
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 base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, San Francisco - 176,600.00 - 239,000.00 USD annually 
USA, GA, Atlanta - 153,600.00 - 207,800.00 USD annually 
USA, IL, Chicago - 153,600.00 - 207,800.00 USD annually 
USA, NJ, Jersey City - 169,000.00 - 228,600.00 USD annually 
USA, NY, New York - 169,000.00 - 228,600.00 USD annually 
USA, TX, Dallas - 153,600.00 - 207,800.00 USD annually 
USA, VA, Herndon - 153,600.00 - 207,800.00 USD annually 
USA, WA, Seattle - 153,600.00 - 207,800.00 USD annually</div>

Senior Delivery Consultant - AI/ML, AWS Professional Services

Opendoor

<div>
 
 About Opendoor
 
 
 
 At Opendoor our mission is to tilt the world in favor of homeowners and those who aim to become one. Homeownership matters. It's how people build wealth, stability, and community. It's how families put down roots, how neighborhoods strengthen, how the future gets built. We're building the modern system of homeownership giving people the freedom to buy and sell on their own terms. We&rsquo;ve built an end-to-end online experience that has already helped thousands of people and we&rsquo;re just getting started.
 
 
 
 About The Role
 
 
 
 Opendoor is seeking an
 
 
 AI/ML Platform Engineer
 
 
 to join our Engineering team in our Seattle, WA office and will play a critical role in our strategic transition to AI-powered pricing models. This high-impact, business-critical position will focus on building the scalable, production-grade platform and infrastructure necessary to support sophisticated ML models, particularly leveraging complex data sources like imagery and video.
 
 
 What You'll Do
 
 
 <ul>
 <li>
 Platform Leadership: Lead the architecture, design, and implementation of the AI/ML feature platform, focusing on scalability, reliability, and high performance for core business systems (e.g., pricing, transaction platforms).
 </li>
 <li>
 Feature Engineering Infrastructure: Design and build large-scale data pipelines responsible for generating, indexing, and versioning AI-derived features (predictions, embeddings) from structured and unstructured data, with a specific emphasis on image and video data.
 </li>
 <li>
 AI Integration: Ensure seamless integration of ML capabilities into production, setting technical standards for real-time AI consumption and agentic optimization within pricing and customer-facing products.
 </li>
 <li>
 Cross-Functional Collaboration: Partner closely with Data Science, Product, and Operations teams to translate business needs into technical requirements, ensuring the platform delivers tangible business outcomes like reduced spreads and increased transaction volume.
 </li>
 <li>
 Mentorship &amp; Direction: Serve as a technical mentor and leader, setting the technical direction and best practices for the new AI/ML platform group.
 
 
 </li>
 </ul>
 What You'll Need
 
 
 <ul>
 <li>
 Extensive experience as a technical leader (Staff/Senior Staff level) in large-scale, production software and data environments.
 </li>
 <li>
 Proven track record of designing and implementing ML/Data Platforms or Feature Stores that directly support production AI/ML models.
 </li>
 <li>
 Deep expertise in distributed systems, cloud infrastructure, and large-scale data processing (e.g., vector search, data versioning).
 </li>
 <li>
 Strong background in data infrastructure and API design, particularly serving data for machine learning consumption.
 </li>
 <li>
 Experience in a domain where AI/ML is critical to the core business (e.g., pricing, optimization, recommendations).
 
 
 </li>
 </ul>
 Highly Sought-After Skills
 
 
 <ul>
 <li>
 Prior experience with computer vision pipelines or handling large-scale image/video data for ML.
 </li>
 <li>
 Familiarity with the technical challenges of managing compute and data versioning to optimize ML iteration cycles.
 </li>
 <li>
 Experience with agentic optimization frameworks.
 
 
 </li>
 </ul>
 
 Compensation
 
 
 
 The base pay range for this position is
 
 
 $247,000.00 - $339,900.00
 
 
 annually, plus RSUs and bonuses. Pay within this range varies by work location and may also depend on your qualifications, job-related knowledge, skills, and experience. We also offer a comprehensive package of benefits including unlimited PTO, medical/dental/vision insurance, life insurance, and 401(k) to eligible employees.
</div>

Software Engineer

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry-leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. 
 
What we do: 
 
<ul><li>Re-invent advertising experiences by bridging human creativity with artificial intelligence</li><li>Transform every aspect of the advertising lifecycle &mdash; from ad creation and optimization to performance analysis and customer insights</li><li>Develop responsible and intelligent AI technologies that balance advertiser needs, enhance the shopping experience, and strengthen the marketplace</li></ul>
Our systems and algorithms operate on one of the world's largest product catalogs, matching shoppers with advertised products with a high relevance bar and strict latency constraints. We work hand-in-hand with Machine Learning and NLP research scientists to deliver highly relevant ads and continuously improve the customer search and detail page experiences. 
 
As a Machine Learning Engineer, you will: 
<ul><li>Drive the technical direction of our offerings across the Sponsored Products organization</li><li>Design, code, troubleshoot, and support scalable ML pipelines and online serving systems</li><li>Work closely with applied scientists to optimize ML model performance and infrastructure</li><li>Implement end-to-end solutions &mdash; what you create is what you own</li></ul> 
We're looking for curious, customer-obsessed engineers with a startup mentality &mdash; those who seek a disruptive yet clear mission, have an owner's mindset, and are relentlessly obsessed with delivering amazing products. 
 
Key job responsibilities 
You will: 
<ul><li>Own technical vision and direction &mdash; Identify problems, develop solutions, and embrace performance metrics to assess system health</li><li>Build and grow your team &mdash; Wear many hats (software design, implementation, project management, operations, business partnerships) and grow leaders within your group</li><li>Collaborate on product direction &mdash; Build strong relationships across engineering, Product, UX, and QA to deliver the right product for customers</li><li>Lead beyond your team &mdash; Contribute to a growing community of engineering leaders, sharing experience and technical acumen to drive org-wide technology decisions</li><li>Own your own shop &mdash; Our products reach hundreds of millions of customers globally; services must meet high standards for operational excellence (24x7x365)</li></ul> 
You are: 
<ul><li>Highly analytical &mdash; You solve problems backed by verifiable data, driving processes, tools, and statistical methods that support rational decision-making</li><li>Team obsessed &mdash; You grow team members, foster creative atmospheres for innovation, and hold engineers accountable for smart decisions and results</li><li>Humbitious &mdash; Ambitious yet humble; you use introspection and feedback to continuously raise the bar</li><li>Engaged by ambiguity &mdash; You explore new problem spaces with unique constraints and non-obvious solutions, quickly identifying gaps and the right people to fill them</li></ul> 
About the team 
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.
</div><h2 class="jobSectionHeader">BASIC QUALIFICATIONS</h2><ul><li>3+ years of non-internship professional software development experience</li><li>3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience</li><li>2+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience</li><li>Knowledge of machine learning model architecture and inference</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques</li><li>Knowledge of ML frameworks including JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, and TensorRT</li><li>1+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience</li><li>Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field</li><li>Experience developing, deploying and managing AI products at scale</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 base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, WA, SEATTLE - 143,700.00 - 194,400.00 USD annually</div>

Machine Learning Engineer, Ad Response Prediction

Explore 283+ Aiml sr machine learning engineer data and ml innovation in Seattle this May. Find roles across top companies and apply now to boost your career.