senior machine learning engineer Jobs in Seattle

senior machine learning engineer

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senior machine learning engineer, ads pangle - usds

senior machine learning engineer, shop ads - usds Jobs in Seattle

senior machine learning engineer, shop ads - usds

software development engineer - ai/ml, aws neuron, multimodal inference Jobs in Seattle

software development engineer - ai/ml, aws neuron, multimodal inference

software engineer

applied machine learning engineer

IUNU

<div>At IUNU (&ldquo;you knew&rsquo;), we&rsquo;re revolutionizing the agriculture industry through cutting-edge AI-driven solutions for greenhouse operations. Our mission is to empower growers with insights that drive operational efficiency, enhance crop yields, and reduce environmental impact. We are seeking an Applied Machine Learning Engineer for our AI team to developing products for our clients and the greenhouse industry.<br>
<br>
Applied Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and programming. If you also have knowledge of data science and software engineering, we&rsquo;d like to meet you. Your ultimate goal will be to shape and build efficient self-learning applications.<br>
<br>
<b>Responsibilities</b><ul><li>
Study and transform data science prototypes</li><li>
Design machine learning systems</li><li>
Research and implement appropriate ML algorithms and tools</li><li>
Develop machine learning applications according to requirements</li><li>
Select appropriate datasets and data representation methods</li><li>
Run machine learning tests and experiments</li><li>
Perform statistical analysis and fine-tuning using test results</li><li>
Train and retrain systems when necessary</li><li>
Extend existing ML libraries and frameworks</li><li>
Keep abreast of developments in the field</li></ul><br>
<b>
Requirements</b><ul><li>
3-5 years of proven experience as a Machine Learning Engineer or a similar role</li><li>
Strong experience with Deep Learning</li><li>
Understanding of data structures, data modeling, and software architecture</li><li>
Deep knowledge of math, probability, statistics, and algorithms</li><li>
Ability to write robust code in Python, Java, and R</li><li>
Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)</li><li>
Excellent communication skills</li><li>
Ability to work in a team</li><li>
Outstanding analytical and problem-solving skills</li><li>
BSc in Computer Science, Mathematics, or a similar field; a Master&rsquo;s degree is a plus</li></ul><br>
<b>
Diversity</b><br>
At IUNU, we&rsquo;re committed to providing a safe and inclusive environment. We are dedicated to the happiness and success of all of our employees, and strive to foster a workplace in which individual differences are recognized, appreciated, nurtured, and respected. Diversity is important, and we strongly encourage people of all identities and backgrounds to confidently apply for a job with us if this is a role that interests and excites you. We want you to feel comfortable bringing your whole self to work with you, with all of your talents and strengths.<p>
</p><p>eJVMiKCwhq</p></div>

Applied Machine Learning Engineer

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
About Sponsored Products and Brands<br>
<br>
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through 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.
<br>
<br>
Sponsored Products Search Relevance&rsquo;s (SPSR) team&rsquo;s mission is to help shoppers easily find and discover the most useful and relevant sponsored products, while improving advertisers&rsquo; ability to find the right shoppers in the right context for their sponsored products. We develop capabilities to understand shoppers&rsquo; queries, shopping missions, and products&rsquo; attributes so that we can identify ASINs that are contextually relevant to the shopper. We make CX/UX improvements so that shoppers can easily perceive why products are relevant to them and efficiently navigate Amazon&rsquo;s vast product selection.<br>
<br>
We are seeking an Applied Science Manager with a strong background in ML and Gen AI solutions. The ideal candidate shall have experience managing both scientists and engineers and will be passionate about applying these technologies to the advertising domain.<br>
<br>
Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we&rsquo;re helping businesses grow on Amazon.com and beyond!<br>
<br>
Key job responsibilities<br>
As an Applied Science Manager, you will:<br>
<br>
<ul><li>Directly manage and lead a cross-functional team of Applied Scientists, Machine Learning Engineers, and Software Development Engineers.</li><li>Develop science and engineering roadmaps for SPB Search Relevance with ML and Gen AI solutions, run annual planning, and foster cross-team collaboration on model development and integration to advertising applications.</li><li>Hire and develop top talent, provide technical and career development guidance to scientists and engineers within and across the organization.</li><li>Stay informed about recent scientific publications, industrial research trends, and system designs that are pertinent to the SPB advertising business and bring those insights with the team.</li></ul><br>
About the team<br>
Sponsored Products Search Relevance&rsquo;s (SPSR) team&rsquo;s mission is to help shoppers easily find and discover the most useful and relevant sponsored products, while improving advertisers&rsquo; ability to find the right shoppers in the right context for their sponsored products. We develop capabilities to understand shoppers&rsquo; queries, shopping missions, and products&rsquo; attributes so that we can identify ASINs that are contextually relevant to the shopper. We make CX/UX improvements so that shoppers can easily perceive why products are relevant to them and efficiently navigate Amazon&rsquo;s vast product selection.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>4+ years of applied research experience</li><li>3+ years of scientists or machine learning engineers management 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>Knowledge of ML, NLP, Information Retrieval and Analytics</li><li>Experience programming in Java, C++, Python or related language</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers</li><li>PhD, or a Master's degree and experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF</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 $165,500/year in our lowest geographic market up to $286,000/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 Science Manager, Sponsored Products and Brands

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company&rsquo;s Think Big leadership principle to the limits. If you&rsquo;re interested in innovating at scale to address big challenges in the world, this is the team for you.
<br>
<br>
Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams.<br>
<br>
We are seeking a Principal Applied Scientist working on machine learning applications in life sciences. This role combines scientific leadership with hands-on innovation, driving solutions from exploratory research through production-ready solutions deployment, while maintaining high scientific standards. You will work with Amazon's large-scale computing resources to accelerate advances in machine learning applications.<br>
<br>
Key job responsibilities<br>
<ul><li>Lead ML for life science efforts using computational design approaches and ML-based tools.</li><li>Guide teams in applying SOTA ML methods, experimentation design, and modeling approaches.</li><li>Transform complex real world problems into scientific challenges and allocate resources effectively.</li><li>Review requirements, conduct technical architecture reviews, and make informed judgments around technical and business tradeoffs.</li><li>Provide mentorship to Applied Scientists, Research Scientists and Data Scientists while maintaining scientific rigor.</li><li>Collaborate with cross functional teams.</li></ul></div><h2 class="jobSectionHeader"><b><br>
BASIC QUALIFICATIONS</b></h2><ul><li>Deep expertise in machine learning, with broad knowledge across biology and life science.</li><li>Strong understanding of scientific methodologies and experimental design.</li><li>Ability to develop production-level code and systems.</li><li>Track record of working with cross-functional scientific teams and fostering collaboration.</li><li>10+ years of relevant, broad research experience after a PhD degree in computer science, computational biology or relevant field .</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience with deep learning frameworks (PyTorch, TensorFlow).</li><li>Familiarity with high-performance computing environments.</li><li>Experience with ML for science and structural biology tools.</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 $179,000/year in our lowest geographic market up to $309,400/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>

Principal Applied Scientist, Amazon Special Projects

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company&rsquo;s Think Big leadership principle to the limits. If you&rsquo;re interested in innovating at scale to address big challenges in the world, this is the team for you.
<br>
<br>
As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for biology. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams.<br>
<br>
Key job responsibilities<br>
<ul><li>Build, adapt and evaluate ML models for life sciences applications</li><li>Collaborate with a cross-functional team of ML scientists, biologists, software engineers and product managers</li></ul></div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD in computer science, machine learning, engineering, or related fields</li><li>Experience with programming languages such as Python, Java, C++</li><li>Expert knowledge of machine learning and deep learning; experience in applying ML to protein biology.</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience using Unix/Linux</li><li>Experience in professional software development</li><li>Experience in patents or publications at top-tier peer-reviewed conferences or journals</li><li>Expert knowledge of protein biology and design.</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, Special Projects

Salesforce

<div><p><i>To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
</i></p><p></p><p>Job Category
</p>Software Engineering
<p></p><p>Job Details
</p><p></p><p><b>About Salesforce
</b></p><p>Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn&rsquo;t a buzzword &mdash; it&rsquo;s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
</p><p></p><p>Ready to level-up your career at the company leading workforce transformation in the agentic era? You&rsquo;re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.
</p><p></p><div><div>Are you passionate about the cutting edge of Artificial Intelligence and eager to shape the future
<br>
of intelligent solutions within Salesforce? We're building a new, dynamic team dedicated to
<br>
exploring, developing, and integrating generative AI and applied AI technologies across our
<br>
products and operations. This is a unique opportunity to lead and contribute to innovative
<br>
projects that will redefine how our internal teams leverage AI to enhance productivity, drive
<br>
insights, and create new capabilities.
<br>
1. What You Will Be Doing
<br>
As a key member of our new Engineering Development and Delivery Applied AI team, you'll be
<br>
instrumental in identifying, evaluating, and implementing AI-driven solutions that address
<br>
critical business challenges and unlock new opportunities within Salesforce. You'll bridge the
<br>
gap between advanced AI research and practical application, focusing on how generative
<br>
models, large language models (LLMs), and other applied AI techniques can be leveraged to
<br>
create intelligent tools, automate complex tasks, and generate novel content or insights. This
<br>
role involves close collaboration with product, engineering, and various internal stakeholders
<br>
to bring these visionary ideas to life.
<br>
2. Responsibilities/Duties
 Solution Design &amp; Development : Design, develop, and deploy generative AI and
<br>
applied AI prototypes as production-ready solutions, leveraging LLMs for code
<br>
generation, content creation, intelligent search, data synthesis, and more.
 Research &amp; Evaluation : Stay abreast of the latest advancements in generative AI,
<br>
applied AI, and machine learning research and techniques, both from within Salesforce&rsquo;s
<br>
own product suite as well as emerging industry tools and research papers. Evaluate new
<br>
models, tools, and platforms for their potential application within Salesforce.
 Cross-Functional Collaboration : Partner with product managers, data scientists,
<br>
engineers, and business stakeholders to gather requirements, define project scopes, and
<br>
ensure successful integration and adoption of AI solutions.
 Performance &amp; Optimization : Monitor and optimize the performance of deployed AI
<br>
models, ensuring scalability, reliability, and continuous improvement.
<br>
3. Skills and Experience
 Technical Expertise :
 At least 5 years of programming experience.
</div></div><div></div><div><div> Strong proficiency in Python and relevant AI/ML frameworks.
 Solid understanding of cloud platforms, specifically AWS, and MLOps principles.
 AI/ML Concepts : Familiarity with core AI/ML concepts, including data preprocessing,
<br>
feature engineering, model training, evaluation, and deployment.
 Generative AI Focus : Practical experience working with Large Language Models (LLMs),
<br>
fine-tuning, prompt engineering, and understanding their applications for text
<br>
generation, summarization, code generation, and conversational AI.
 Services and Security : A strong understanding of developing and delivering services on
<br>
cloud platforms like AWS, including concepts around cloud security, identity and access
<br>
management, data protection, and network security.
 Problem-Solving : Excellent analytical and problem-solving skills, with the ability to
<br>
translate complex business problems into viable AI solutions.
 Communication : Strong verbal and written communication skills, capable of explaining
<br>
complex technical concepts to non-technical stakeholders and providing content that
<br>
can be understood by both humans and models.
 Teamwork : Proven ability to work effectively in a collaborative, fast-paced team
<br>
environment.
 Education : Bachelor's or Master's degree in Computer Science, Artificial Intelligence,
<br>
Machine Learning, Data Science, or a related technical field.
<br>
4. Preferred Requirements
 Knowledge of various machine learning models, including deep learning architectures,
<br>
particularly those related to natural language processing (NLP) and generative models.
 Experience with Salesforce platform technologies, specifically Apex, Agentforce, and
<br>
Data Cloud.
 Prior experience in a leadership or mentorship role within an engineering development
<br>
team.
</div></div><p></p><p>Unleash Your Potential
</p><p>When you join Salesforce, you&rsquo;ll be limitless in all areas of your life. Our benefits and resources support you to find balance and <i>be your best </i>, and our AI agents accelerate your impact so you can <i>do your best </i>. Together, we&rsquo;ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future &mdash; but to redefine what&rsquo;s possible &mdash; for yourself, for AI, and the world.
</p><p></p><p>Accommodations
</p><p>If you require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form .
</p><p></p><p>Posting Statement
</p><p>Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that&rsquo;s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications &ndash; without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.
</p><p></p>In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.
<p></p>For Washington-based roles, the base salary hiring range for this position is $184,000 to $253,000.</div><p></p>

Software Engineering LMTS

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><p>
At Amazon Selection and Catalog Systems (ASCS), our mission is to power the online buying experience for customers worldwide so they can find, discover, and buy any product they want. We innovate on behalf of our customers to ensure uniqueness and consistency of product identity and to infer relationships between products in Amazon Catalog to drive the selection gateway for the search and browse experiences on the website. We're solving a fundamental AI challenge: establishing product identity and relationships at unprecedented scale. Using Generative AI, Visual Language Models (VLMs), and multimodal reasoning, we determine what makes each product unique and how products relate to one another across Amazon's catalog. The scale is staggering: billions of products, petabytes of multimodal data, millions of sellers, dozens of languages, and infinite product diversity&mdash;from electronics to groceries to digital content.<br>
<br>
The research challenges are immense. GenAI and VLMs hold transformative promise for catalog understanding, but we operate where traditional methods fail: ambiguous problem spaces, incomplete and noisy data, inherent uncertainty, reasoning across both images and textual data, and explaining decisions at scale. Establishing product identities and groupings requires sophisticated models that reason across text, images, and structured data&mdash;while maintaining accuracy and trust for high-stakes business decisions affecting millions of customers daily.<br>
<br>
Amazon's Item and Relationship Platform group is looking for an innovative and customer-focused applied scientist to help us make the world's best product catalog even better. In this role, you will partner with technology and business leaders to build new state-of-the-art algorithms, models, and services to infer product-to-product relationships that matter to our customers. You will pioneer advanced GenAI solutions that power next-generation agentic shopping experiences, working in a collaborative environment where you can experiment with massive data from the world's largest product catalog, tackle problems at the frontier of AI research, rapidly implement and deploy your algorithmic ideas at scale, across millions of customers.<br>
<br>
Key job responsibilities<br>
Formulate novel research problems at the intersection of GenAI, multimodal learning, and large-scale information retrieval&mdash;translating ambiguous business challenges into tractable scientific frameworks<br>
<br>
Design and implement systems leveraging VLMs, foundation models, and agentic architectures to solve product identity, relationship inference, and catalog understanding at billion-product scale<br>
<br>
Pioneer explainable AI methodologies that balance model performance with scalability requirements for production systems impacting millions of daily customer decisions<br>
<br>
Optimize and scale large-language-model inference pipelines, including model compression, parallelization, and workflow orchestration, to support massive-volume LLM workflows with low latency and high reliability.<br>
<br>
Define research roadmaps aligned with business priorities, balancing foundational research with incremental product improvements<br>
<br>
Mentor junior scientists and engineers on advanced ML techniques, experimental design, and scientific rigor&mdash;building organizational capability in GenAI and multimodal AI<br>
<br>
Represent the team in the broader science community&mdash;publishing findings, delivering tech talks, and staying at the forefront of GenAI, VLM, and agentic system research</p><h2 class="jobSectionHeader"><b>
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>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>
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>

Senior Applied Scientist

Uber

<div><b>About the Role</b>
<br>
<br>
The Reserve product is a maturing product, most of the low hanging fruit&quot; initiatives to improve the experience to consistently deliver high reliability have been delivered. Currently, our focus is in building smart levers to maintain reliability while driving efficiency, improving our unit economics and growing adoption and retention.
<br>
<br>
Some of the key projects involve major changes in Pricing, Matching and Dispatch that involve transitioning from heuristic based decision making to building machine learning models to make key decisions in real time, as well as important changes to Driver and Rider experience, including discoverability and awareness generation levers, and finally piloting new use cases that leverage the Reserve Tech as a platform to unlock new vectors of growth.
<br>
<br>
<b>What You Will Do</b>
<br>
<ul><li>Deploy a wide variety of methodologies, including causal inference techniques, experiments, funnel analyses, ML modeling and Optimization algorithms to solve real world business and customer problems.
</li><li>Work together with Product, Operations, and Engineering partners to design a roadmap of features and initiatives as well as the long-term team strategy
</li><li>Present findings to technical and non-technical audiences.
</li></ul>- Basic Qualifications -
<br>
<ul><li>Ph.D., M.S. or Bachelor's degree in Statistics, Mathematics, Computer Science, Machine Learning, Operations Research, or other quantitative fields.
</li><li>2+ years of industry experience as an Applied or Data Scientist or equivalent (not required with Ph.D.).
</li><li>Proficiency in programming languages (Python, Java, Scala) and ML frameworks (TensorFlow, PyTorch, Scikit-Learn), underpinned by a solid grasp of MLOps practices, including design documentation, testing, and source code management with Git.
</li><li>Good understanding of experimental design and analysis (e.g., A/B and market-level experiments), causal inference.
</li><li>Good business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions.
</li></ul>- Preferred Qualifications -
<br>
<ul><li>Ability to drive clarity on the best modeling or analytic solution for a business objective
</li><li>Experience in building statistical, optimization, and machine learning models for a range of applications.
</li><li>Expertise in causal inference, A/B testing designs, multivariate testing, and other advanced analytical methods.
</li><li>Experience in designing highly scalable, resilient systems for customer-facing applications and familiarity with optimization techniques.
</li><li>Propose, design, and analyze large scale online experiments and interpret the results to draw detailed and actionable conclusions.
</li>Collaborate with cross-functional teams across disciplines such as product, engineering, operations, and marketing to drive system development end-to-end from ideation to productionization<br>
<li>
</li></ul><br>
<br>
<br>
<br>
For Seattle, WA-based roles: The base salary range for this role is USD$155,000 per year - USD$172,000 per year. 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>

Scientist II - Reservations

Explore 115+ Applied machine learning engineer in Seattle this December. Find roles across top companies and apply now to boost your career.