medical laboratory scientist Jobs in Seattle

medical laboratory scientist

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

aiml - sr machine learning engineer - data and ml innovation

applied scientist

applied scientist, alexa enterprise Jobs in Seattle

applied scientist, alexa enterprise

applied scientist, prime video Jobs in Seattle

applied scientist, prime video

machine learning scientist

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Are you looking for an opportunity to build an LLM-based enterprise-grade, highly available, large scale solution? Does it excite you to find patterns and build generic, composable solutions to solve complex problems? Are you looking for inventing newer and simpler ways of building solutions? If so, we are looking for you to fill a challenging position in Alexa Enterprise (AE) team. AE brings the power of Alexa voice assistant to enterprise partners in industries such as hospitality and senior living. We tackle pressing challenges like workforce shortage. We are inventing Large Language Models (LLM)-driven interactions to create memorable moments for users while simultaneously boosting partner revenues and reinforcing brand identity. Beyond managed properties, AE extends Alexa's reach to premium third-party devices, seamlessly integrating with household names like Samsung, LG, and Sonos, thus amplifying its impact across diverse ecosystems.<br>
<br>
AE team is looking for a passionate, highly skilled and inventive Applied Scientist, with a strong machine learning background, to lead the development and implementation of state-of-the-art ML systems for Alexa Enterprise use cases.
<br>
<br>
As an Applied Scientist in the team, you will play a critical role in driving the development of conversational assistants, in particular those based on Large Language Models (LLM's), that meet enterprise standards. You will handle Amazon-scale use cases with significant impact on our customers' experiences.<br>
<br>
Key job responsibilities<br>
<ul><li>You will analyze, understand and improve user experiences by leveraging Amazon&rsquo;s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence</li><li>You will work on core LLM technologies, including developing best-in-class modeling, prompt optimization algorithms to enable Conversation AI use cases</li><li>Build and measure novel online &amp; offline metrics for personal digital assistants and customer scenarios, on diverse devices and endpoints</li><li>Create, innovate, and deliver deep learning, policy-based learning, and/or machine learning-based algorithms to deliver customer-impacting results</li><li>Perform model/data analysis and monitor metrics through online A/B testing</li></ul></div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>3+ years of building models for business application experience</li><li>PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience using Unix/Linux</li><li>Experience in professional software development</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
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.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Applied Scientist, Alexa Enterprise

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
If you are interested in this position, please apply on Twitch's Career site https://www.twitch.tv/jobs/en/<br>
<br>
About Us:<br>
<br>
Twitch is the world&rsquo;s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day.<br>
We&rsquo;re about community, inside and out. You&rsquo;ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We&rsquo;re on a quest to empower live communities, so if this sounds good to you, see what we&rsquo;re up to on LinkedIn and X, and discover the projects we&rsquo;re solving on our Blog. Be sure to explore our Interviewing Guide to learn how to ace our interview process.<br>
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interviewing tips on Instagram, and discover projects we're solving on our Blog.<br>
<br>
About the Role<br>
<br>
We are looking for an Applied Scientist to solve challenging and open-ended problems in the domain of recommendations, search, ranking and information retrieval. As an Applied Scientist on Twitch's Community team, you will use ML to help viewers find streamers and communities they&rsquo;ll love. You will collaborate with a team of passionate scientists and engineers to develop these models and put them into production, where they can help Twitch's creators and viewers succeed and build communities.<br>
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You will report to the Applied Science Manager on the Community Discovery Team.<br>
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You can work in San Francisco, CA or Seattle, WA.
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<br>
You Will<br>
<br>
<ul><li>Develop ML algorithms for recommendations, ranking and search problems that can improve discovery on Twitch.</li><li>Collaborate with senior scientists and engineers to deploy ML code in production.</li><li>Collaborate with our Product and Engineering teams to work backwards from customer discovery problems, in order to determine the ML solution (algorithm and pipeline) that will have the biggest impact on our user base in the real world.</li><li>Participate in the scientific community at Twitch, Amazon, and the broader ML and risk community.</li></ul><br>
Perks<br>
<ul><li>Medical, Dental, Vision &amp; Disability Insurance</li><li>401(k)</li><li>Maternity &amp; Parental Leave</li><li>Flexible PTO</li><li>Amazon Employee Discount</li></ul></div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>BS or MS or PhD in Computer Science, Machine Learning, Data Science, Statistics, Mathematics, with relevant industry experience. We welcome applicants with non-traditional backgrounds. We welcome applicants with non-traditional backgrounds.</li><li>Hands-on experience with predictive modeling and analysis to solve real-world problems.</li><li>Proficiency with Python and Deep Learning Frameworks such as PyTorch or Tensorflow, basic proficiency with SQL.</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>MS/PhD in relevant fields or a Degree with a specialization in Machine Learning.</li><li>Experience shipping your models to production.</li><li>1+ years of experience working in recommendations or search.</li><li>Papers in top ML conferences of journals such as Neurips, Recsys, ICLR, ICML etc.</li><li>Familiarity with Twitch, its business, and its community.</li></ul><br>
Twitch is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
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.<br>
<br>
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.<br>
<br>
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.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,400/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Applied Scientist

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by protecting Amazon customers from hackers and bad actors? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer every day? Are you excited by the prospect of analyzing and modeling terabytes of data and create state-of-art algorithms to solve real world problems? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Amazon Account Integrity team.<br>
<br>
The Amazon Account Integrity team works to ensure that customers are protected from scams and from bad actors trying to access their accounts. Our greatest challenge is protecting customer trust without unjustly harming good customers. To strike the right balance, we invest in mechanisms which allow us to accurately identify and mitigate risk, and to quickly correct and learn from our mistakes. This strategy includes continuously evolving enforcement policies, iterating our Machine Learning risk models, and exercising high&#8208;judgement decision&#8208;making where we cannot apply automation.<br>
<br>
Key job responsibilities<br>
<ul><li>Use statistical and machine learning techniques to create scalable risk and scam detection systems</li><li>Analyzing and understanding large amounts of Amazon&rsquo;s historical business data for specific instances of risk or broader fraud trends</li><li>Design, development and evaluation of highly innovative models for risk management</li><li>Working closely with software engineering teams to drive real-time model implementations and new feature creations</li><li>Working closely with operations staff to optimize risk management operations</li><li>Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation</li><li>Tracking general business activity and providing clear, compelling management reporting on a regular basis</li><li>Research and implement novel machine learning and statistical approaches</li></ul></div><h2 class="jobSectionHeader"><b><br>
BASIC QUALIFICATIONS</b></h2><ul><li>4+ years of applied research experience</li><li>3+ years of building machine learning models for business application experience</li><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with neural deep learning methods and machine learning</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.</li><li>PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field</li><li>Experience in applied research</li><li>Experience with building Generative AI and Agentic AI systems</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
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.<br>
<br>
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.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Applied Scientist, Account Integrity

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Selling Partner Experience (SPX) organization strives to make Amazon the best place for Selling Partners to do business. The SPX AI Lab team is building the AI capabilities powering the Selling Assistant, Amazon's conversational assistant experience for Selling Partners. The Selling Assistant is a trusted partner and a seasoned advisor that&rsquo;s always available to enable our partners to thrive in Amazon&rsquo;s stores. It takes away the cognitive load of selling on Amazon by providing a single interface to handle a diverse set of selling needs. The assistant always stays by the seller's side, talks to them in their language, enables them to capitalize on opportunities, and helps them accomplish their business goals with ease. It is powered by the latest advances in Generative AI, going beyond a typical chatbot to provide an intuitive, intelligent, and personalized experience to sellers running real businesses, large and small.<br>
<br>
Do you want to join an innovative group of scientists, engineers, and product managers who use state-of-the-art Generative AI and Machine Learning technologies to help Amazon create a delightful Selling Partner experience? Do you want to build solutions to real business problems by automatically understanding and addressing sellers&rsquo; challenges, needs and opportunities? Are you excited by the prospect of contributing to one of Amazon&rsquo;s most strategic Generative AI initiatives? If yes, then you may be a great fit to join the SPX AI Lab team.<br>
<br>
Key job responsibilities<br>
<ul><li>Use state-of-the-art Machine Learning and Generative AI techniques to create the next generation of the tools that empower Amazon's Selling Partners to succeed.</li><li>Design, develop and deploy highly innovative models to interact with Sellers and delight them with solutions.</li><li>Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features.</li><li>Establish scalable, efficient, automated processes for large scale data analyses, model benchmarking, model validation and model implementation.</li><li>Research and implement novel machine learning and statistical approaches.</li><li>Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment.</li></ul><br>
About the team<br>
SPX AI Lab is a growing team of scientists driving the research and development of the next generation of GenAI experiences that empower Amazon's Selling Partners to succeed. We draw from many science domains, from Natural Language Processing to Computer Vision to Optimization to Economics, to create solutions that seamlessly and automatically engage with Sellers, solve their problems, and help them grow. We strive to radically simplify the seller experience, lowering the cognitive burden of selling on Amazon by making it easy to accomplish critical tasks such as launching new products, understanding and complying with Amazon&rsquo;s policies and taking actions to grow their business.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience</li><li>3+ years of building machine learning models or developing algorithms for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience in patents or publications at top-tier peer-reviewed conferences or journals</li><li>Experience in investigating, designing, prototyping, and delivering new and innovative system solutions</li><li>Experience in developing Generative AI applications.</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
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.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Applied Scientist, SPX AI Lab

Fred Hutchinson Cancer Center

<div><div><div><div><div><div><div>Job ID</div>
<div>30057
</div></div><div><div>Type</div>
<div>Regular Full-Time
</div></div><div><div>Location
</div><div>US-WA-Seattle
</div></div><div><div>Category</div>
<div>Biostatistics, Bioinformatics and Computational Biology
</div></div></div></div></div></div><h2 class="jobSectionHeader"><b>Overview
</b></h2><div><div><div><div>Fred Hutchinson Cancer Center is an independent, nonprofit organization providing adult cancer treatment and groundbreaking research focused on cancer and infectious diseases. Based in Seattle, Fred Hutch is the only National Cancer Institute-designated cancer center in Washington.</div><div></div><div><br>
With a track record of global leadership in bone marrow transplantation, HIV/AIDS prevention, immunotherapy and COVID-19 vaccines, Fred Hutch has earned a reputation as one of the world&rsquo;s leading cancer, infectious disease and biomedical research centers. Fred Hutch operates eight clinical care sites that provide medical oncology, infusion, radiation, proton therapy and related services, and network affiliations with hospitals in five states. Together, our fully integrated research and clinical care teams seek to discover new cures to the world&rsquo;s deadliest diseases and make life beyond cancer a reality.</div><div></div><div><br>
At Fred Hutch we value collaboration, compassion, determination, excellence, innovation, integrity and respect. Our mission is directly tied to the humanity, dignity and inherent value of each employee, patient, community member and supporter. Our commitment to learning across our differences and similarities make us stronger. We seek employees who bring different and innovative ways of seeing the world and solving problems.</div><div></div><div><br>
The goal of its Public Health Sciences Division, which is home to the nation&rsquo;s oldest program devoted to cancer prevention research, is to identify strategies that would ultimately reduce the incidence of and mortality from cancer and other diseases.</div>
</div></div></div><h2 class="jobSectionHeader"><b>Responsibilities
</b></h2><div><div><div><p>The successful applicant will work closely with Dr. Yingqi Zhao, and other collaborators to develop statistical and machine learning methods for medical decision-making in cancer prevention and early detection. Key areas of focus include, but are not limited to, designing clinical decision rules for cancer early detection using real-world data such as Electronic Medical Records (EMRs), developing AI tools for integrating multimodal data in early detection, and developing EMR-based algorithms to identify high-risk populations. The applicant will have the opportunity to engage in research across a wide range of statistical areas and will gain access to data from various real-world studies. These efforts will result in both methodological and collaborative publications in high-quality, peer-reviewed journals.</p>
</div></div></div><h2 class="jobSectionHeader"><b>Qualifications
</b></h2><div><div><div><div><b>MINIMUM QUALIFICATIONS:</b></div><ul><li>
Suitable applicants should complete (or nearly complete) a Ph.D. or equivalent in Statistics, Biostatistics, or a similar quantitative field prior to their appointment.</li><li>
The candidate should have solid training in statistical methods and computational skills.</li><li>
Experience with real-world data analysis, AI and machine learning, causal inference, and precision medicine are plus.</li></ul><div>
Please include the following materials in your application:</div><ul><li>
CV;</li><li>
Two (2) publication samples or preprints;</li><li>
Contact information for three (3) references.</li></ul><p></p><div>
The annual base salary range for this position is from $77,976 to $95,014, and pay offered will be based on experience and qualifications.</div><div></div><div><br>
This position may be eligible for relocation assistance.</div><div><br>
Fred Hutchinson Cancer Center offers employees a comprehensive benefits package designed to enhance health, well-being, and financial security. Benefits include medical/vision, dental, flexible spending accounts, life, disability, retirement, family life support, employee assistance program, onsite health clinic, income-based child care subsidy, tuition reimbursement, paid vacation (22 days per year), paid sick leave (up to 30 calendar days per occurrence of a qualifying reason), paid holidays (13 days per year), and paid parental leave (up to 4 weeks).</div>
</div></div></div><h2 class="jobSectionHeader"><b>Additional Information
</b></h2><div><div><div>We are proud to be an Equal Employment Opportunity (EEO) and Vietnam Era Veterans Readjustment Assistance Act (VEVRAA) Employer. We do not discriminate on the basis of race, color, religion, creed, ancestry, national origin, sex, age, disability (physical or mental), marital or veteran status, genetic information, sexual orientation, gender identity, political ideology, or membership in any other legally protected class. We desire priority referrals of protected veterans. If due to a disability you need assistance/and or a reasonable accommodation during the application or recruiting process, please send a request to Human Resources at hrops@fredhutch.org or by calling 206-667-4700.
</div></div></div><div><h2 class="jobSectionHeader"><b>Options</b></h2>
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Post-Doctoral Research Fellow

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
As a part of our team, you will bring deep expertise in quantitative modeling (forecasting, recommender systems, reinforcement learning, causal inferencing or generative artificial intelligence) to build and refine models that can be implemented in production. You will be a thought leader as we chart new courses with our ad sales support technologies, and you have the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers. As a senior lead, you will have the excitement to take iterative approaches to tackle big, long-term problems.<br>
<br>
Why you will love this opportunity: Amazon has invested heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon's Retail and Marketplace businesses. We deliver billions of ads impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit with a broad mandate to experiment and innovate.<br>
<br>
Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences; this is your opportunity to work within the fastest growing businesses across all of Amazon! Define a long-term scientific vision for our advertising sales business, driven from our customers' needs, translating that direction into specific plans for scientists, engineers and product teams. This role combines scientific leadership, organizational ability, technical strength, product focus, and business understanding.<br>
<br>
Key job responsibilities<br>
<ul><li>Conceptualize and lead state-of-the-art research on new Machine Learning and Generative Artificial Intelligence solutions to optimize all aspects of the Ad Sales business</li><li>Guide the technical approach for the design and implementation of successful models and algorithms in support of expert cross-functional teams delivering on demanding projects</li><li>Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities</li><li>Run regular A/B experiments, gather data, and perform statistical analysis</li><li>Work closely with software engineers to deliver end-to-end solutions into production</li><li>Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving</li></ul><br>
About the team<br>
Sales AI is a central science and engineering organization within Amazon Advertising Sales that powers selling motions and account team workflows via state-of-the-art of AI/ML services. Sales AI is investing in a range of sales intelligence models, including the development of advertiser insights, recommendations and Generative AI-powered applications throughout account team workflows.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>5+ years of building machine learning models for business application experience</li><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with neural deep learning methods and machine learning</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.</li><li>Experience with large scale distributed systems such as Hadoop, Spark etc.</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
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.<br>
<br>
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.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Sr. Applied Scientist, D&S

Uber

<div><b>About the Role</b>
<br>
<br>
Have you ever ordered a car service on Uber, and when the ride arrives, wondered how it got to you so fast? Ever ordered food on UberEats and wondered where the driver was before receiving your order and how long it took to get to the restaurant or if your order was ready when the courier arrived? Ever wondered why your grocery delivery from Uber always has the best apple picked?
<br>
<br>
If so, Uber is for you. In our ML and Science division, we strive to make magic within Uber's marketplace. This requires judgment to make difficult trade-offs, blending algorithms with human resourcefulness, and the ability to build simplicity from complexity. When we get the balance right for everyone, Uber magic happens. We build systems to peer into the future to craft the most cost-efficient marketplace for matching supply and demand. We are passionate about using innovative economics, machine learning, and scalable distributed software that automates and optimizes every aspect of this intricate dance between participants of the marketplace.
<br>
<br>
We are involved in every stage of the product development cycle and use data to inform product decisions, build models to power our solutions, and also develop platform tools that are used across teams with a primary focus on Mobility and Delivery. We work with millions of earners across the globe to make this magic happen and want you to join us!
<br>
<br>
<b>About the Team</b>
<br>
<br>
Earners (drivers and couriers) are an integral part of Uber's multi-sided marketplace. They provide the time and the means to move people and things. Importantly, they enable the connection between the physical and digital world to make the movement happen at the push of a button for everyone, everywhere.
<br>
<br>
Within Uber, Earner Growth plays a critical role in earners' journey as the team is responsible for earner onboarding, activation, early life cycle, and resurrection. This presents the teams with the opportunity to shape and tailor the product experience during earners' many firsts (i.e., first time interacting on the Uber platform, choosing the earning opportunity, going online, receiving incentive offers, completing a trip, or reading the earnings summary). These firsts can be daunting.
<br>
<br>
Therefore, making sure that the earner journey is great at every touch point is important to build trust with Earners, communicate Uber's value proposition, and ensure each firsts to be a great experience.
<br>
<br>
<b>What You'll Do</b>
<ul><li>Build statistical, optimization, and machine learning models
</li><li>Develop innovative new earner incentives that earners for choosing our network and optimizing Uber's new earner incentives spend
</li><li>Optimize Uber's background check spend and onboarding funnel
</li><li>Design recommendation engines to recommend the most relevant earning opportunities and early lifecycle content
</li><li>Develop matching algorithms for driver to driver mentorship program
</li><li>Model and predict earner behaviors to improve earner experience throughout the onboarding funnel
</li><li>The team employs a variety of ML/AI techniques, spanning from causal ML meta learners, supervised ML, RL multi-armed bandits, genAI LLM to deep learning embeddings to build impactful data products.
</li><li>Work closely with multi-functional leads to develop technical vision, new methodological approaches, and drive team direction.
</li><li>Collaborate with cross-functional teams such as product, engineering, operations, and marketing to drive ML system development end-to-end from conceptualization to final product.
</li></ul><b>Basic Qualifications</b>
<ul><li>PhD or equivalent experience in Computer Science, Machine Learning, Operations Research, Statistics, or other related quantitative fields or related field
</li><li>4 years minimum of industry experience as a Machine Learning Engineer/Research Scientist with a strong focus on deep learning and probabilistic modeling.
</li><li>Proficiency in multiple object-oriented programming languages (e.g. Python, Go, Java, C++).
</li><li>Experience with any of the following: Spark, Hive, Kafka, Cassandra.
</li><li>Experience building and productionizing innovative end-to-end Machine Learning systems.
</li><li>Experience in exploratory data analysis, statistical modeling, hypothesis testing, and experimental design.
</li><li>Experience working with cross-functional teams(product, science, product ops etc).
</li></ul><b>Preferred Qualifications</b>
<ul><li>5+ years of industry experience in machine learning, including building and deploying ML models.
</li><li>Publications at industry recognized ML conferences.
</li><li>Experience in modern deep learning architectures and probabilistic modeling.
</li><li>Experience with optimization techniques, including reinforcement learning (RL), Bayesian methods, causal ML meta learners, genAI LLM.
</li>Expertise in the design and architecture of ML systems and workflows.<br>
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</li></ul><br>
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For New York, NY-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 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. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.</div>

Sr. Machine Learning Engineer, Earner Growth

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