397 Data Scientists jobs in Seattle

Onsite Role Software Engineer Tech Lead As a Software Engineer Tech Lead, you will be responsible for leading a team of software engineers in an initiative to migrate an on-premises large-scale data warehouse and associated data pipelines to Azure. You will have core competencies in the big data analytics platforms including Spark/Databricks as well as Data Warehouse/Data Lake.

At Qualtrics, we create software the world’s best brands use to deliver exceptional frontline experiences, build high-performing teams, and design products people love. But we are more than a platform—we are the creators and stewards of the Experience Management category serving over 18K clients globally. Building a category takes grit, determination, and a disdain for convention—but most of all it requires close-knit, high-functioning teams with an unwavering dedication to serving our customers. When you join one of our teams, you’ll be part of a nimble group that’s empowered to set aggressive goals and move fast to achieve them. Strategic risks are encouraged and complex problems are solved together, by passing the mic and iterating until the best solution comes to light. You won’t have to look to find growth opportunities—ready or not, they’ll find you. From retail to government to healthcare, we’re on a mission to bring humanity, connection, and empathy back to business. Join over 5,000 people across the globe who think that’s work worth doing. Machine Learning Engineer Why We Have This Role We are looking for an engineer to bring our Machine Learning and Artificial Intelligence R&D strategy to the next level. Our goal is to personalize the Qualtrics experience using ML and AI features showcasing Qualtrics data as a core value proposition and competitive advantage. You should love building simple solutions to solve hard customer problems. Crafting systems in an agile environment to withstand hyper growth and owning quality from end to end is a rewarding challenge and one of the reasons Qualtrics is such an exciting place to work! How You’ll Find Success Work in a supportive environment enables individual growth and achievement of team goals Collaborate with your peers, prioritize features, and work with a sense of urgency to deliver value to our customers Develop scalable, robust, and highly available micro services to perform simple to complex statistical analyses and build/deploy machine learning models Implement new features and optimize existing ones to delight our customers How You’ll Grow Work in a multi-disciplinary team to implement, tune, and productize cutting-edge machine learning models to meet the demands of our rapidly growing business Build and maintain highly scalable data pipelines to cleanse, anonymize, measure, and index complex and multi-modal data. Things You’ll Do Work closely with, and incorporate feedback from other specialists, tech-ops, and product managers Lead and engage in design reviews, architectural discussions, requirement definitions and other technical activities in diverse capacity Attend daily stand-up meetings, collaborate with your peers, prioritize features, and work with a sense of urgency to deliver value to your customers Finding quick ways to prototype and test possible solutions to large problems What We’re Looking For On Your Resume Bachelor’s degree in Computer Science or related fields. Interest in modern machine learning / deep learning systems Strong Computer Science fundamentals in algorithm design, complexity analysis, and performance Experience in programming with at least one modern programming language such as Java, C# or Python, including object-oriented design Experience with applied machine learning models and large-scale ML systems What You Should Know About This Team The Data Intelligence Center of Excellence (DICE) organization provides AI/ML research and development services for all product lines. This team builds core machine learning infrastructure and services. We partner with application teams to deliver ML algorithms and models that drive efficiency, innovation, and growth. Our Team’s Favorite Perks and Benefits $1800 Experience bonus to be used for an “Experience” of your choosing Unlimited Sick Days Amazing QGroup Communities; MOSAIQ, Green Team, Qualtrics Pride, Q&Able, Qualtrics Salute, and Women’s Leadership Development, which exist as places for support, allyship, and advocacy. The Qualtrics Hybrid Work Model: Our hybrid work model is elegantly simple: we all gather in the office three days a week; Mondays and Thursdays, plus one day selected by your organizational leader. These purposeful in-person days in thoughtfully designed offices help us do our best work and harness the power of collaboration and innovation. For the rest of the week, work where you want, owning the integration of work and life. Qualtrics is an equal opportunity employer meaning that all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other protected characteristic. Applicants in the United States of America have rights under Federal Employment Laws: Family & Medical Leave Act , Equal Opportunity Employment , Employee Polygraph Protection Act Qualtrics is committed to the inclusion of all qualified individuals. As part of this commitment, Qualtrics will ensure that persons with disabilities are provided with reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please let your Qualtrics contact/recruiter know. Not finding a role that’s the right fit for now? Qualtrics Insiders is the one-stop shop for all things Qualtrics Life. Sign up for exclusive access to content created with you in mind and get the scoop on what we have going on at Qualtrics - upcoming events, behind the scenes stories from the team, interview tips, hot jobs, and more. No spam - we promise! You'll hear from us two times a month max with fresh, totally tailored info - so be sure to stay connected as you explore your best role and company fit. For full-time positions, this pay range is for base per year; however, base pay offered may vary depending on location, job-related knowledge, education, skills, and experience.A sign-on bonus and restricted stock units may be included in an employment offer, in addition to a range of medical, financial, and other benefits, based on eligibility criteria. Washington State Annual Pay Transparency Range $9,500 — $1 7,000 USD #J-18808-Ljbffr

Company Overview Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM). What you'll do Docusign is looking for a passionate, talented, and collaborative Machine Learning Engineer to join their AI Infrastructure team. This team builds DocuSign's centralized platform for creating, managing, and deploying advanced AI/ML solutions to enhance customer journeys within the Docusign Agreement Cloud. As a Machine Learning Engineer, you'll support all aspects of the machine learning lifecycle, including the research platform, training and deployment pipelines, and labeling and serving infrastructure. You'll also partner with expert applied researchers specializing in areas like document understanding, natural language processing (NLP), and computer vision to prototype and productionize solutions for real business use cases at scale. This is an individual contributor role reporting to the Senior Manager, Machine Learning. Responsibility Collaborate with Applied Science, Product and other engineers across multiple offices and time zones to create and deliver new machine learning products and features on time Contribute to the development of AI infrastructure by building highly scalable gRPC-based services to enable offline and online machine learning pipelines, ensuring enterprise-grade security and reliability Develop systems to optimize and create AI-assisted data labeling processes while maintaining appropriate and thorough data governance and security standards Contribute to the development of scalable model training infrastructure to minimize the time it takes to deploy the candidate models to production Optimize model performance (including open source and licensed LLMs) in production leveraging best practices for CPU/GPU inference on NVIDIA Triton with TensorRT / ONNX Improve platform observability by implementing tools and required infrastructure to monitor and analyze the performance of deployed AI services Job Designation Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation) Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law. What you bring Basic Minimum of 5 years of related experience with a Bachelor’s degree; or 3 years of related experience with a Master’s degree; or a PhD without experience; or equivalent experience Experience building/consuming RESTful and gRPC based web-services Experience with CI/CD build pipelines, integrated tests, and test-driven development Experience with cloud deployment technologies, such as Kubernetes or Docker containers Experience with designing and scaling fullstack or distributed backend systems Experience with Java, Python or similar programming languages Preferred Experience building machine learning products, data pipelines, or machine learning training and deployment systems Experience with deployment and monitoring of machine learning models Ability and desire to move across technology stacks fluently and easily Experience with LLMs Familiarity with NLP, Computer Vision domains Familiarity with Open AI APIs and libraries Wage Transparency Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience. Based on applicable legislation, the below details pay ranges in the following locations: California: $157,500.00 - $54,350.00 base salary Washington, Maryland, New Jersey and New York (including NYC metro area): 151,200.00 - 222,450.00 base salary This role is also eligible for the following: Bonus: Sales personnel are eligible for variable incentive pay dependent on their achievement of pre-established sales goals. Non-Sales roles are eligible for a company bonus plan, which is calculated as a percentage of eligible wages and dependent on company performance. Stock: This role is eligible to receive Restricted Stock Units (RSUs). Global benefits provide options for the following: Paid Time Off: earned time off, as well as paid company holidays based on region Paid Parental Leave: take up to six months off with your child after birth, adoption or foster care placement Full Health Benefits Plans: options for 100% employer paid and minimum employee contribution health plans from day one of employment Retirement Plans: select retirement and pension programs with potential for employer contributions Learning and Development: options for coaching, online courses and education reimbursements Compassionate Care Leave: paid time off following the loss of a loved one and other life-changing events Life at Docusign Working here Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At Docusign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live. Accommodation Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at . If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at for assistance. Applicant and Candidate Privacy Notice States Not Eligible for Employment This position is not eligible for employment in the following states: Alaska, Hawaii, Maine, Mississippi, North Dakota, South Dakota, Vermont, West Virginia and Wyoming. Equal Opportunity Employer It's important to us that we build a talented team that is as diverse as our customers and where all employees feel a deep sense of belonging and thrive. We encourage great talent who bring a range of perspectives to apply for our open positions. Docusign is an Equal Opportunity Employer and makes hiring decisions based on experience, skill, aptitude and a can-do approach. We will not discriminate based on race, ethnicity, color, age, sex, religion, national origin, ancestry, pregnancy, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, registered domestic partner status, caregiver status, marital status, veteran or military status, or any other legally protected category. EEO Know Your Rights poster #LI-Hybrid Basic Minimum of 5 years of related experience with a Bachelor’s degree; or 3 years of related experience with a Master’s degree; or a PhD without experience; or equivalent experience Experience building/consuming RESTful and gRPC based web-services Experience with CI/CD build pipelines, integrated tests, and test-driven development Experience with cloud deployment technologies, such as Kubernetes or Docker containers Experience with designing and scaling fullstack or distributed backend systems Experience with Java, Python or similar programming languages Preferred Experience building machine learning products, data pipelines, or machine learning training and deployment systems Experience with deployment and monitoring of machine learning models Ability and desire to move across technology stacks fluently and easily Experience with LLMs Familiarity with NLP, Computer Vision domains Familiarity with Open AI APIs and libraries Docusign is looking for a passionate, talented, and collaborative Machine Learning Engineer to join their AI Infrastructure team. This team builds DocuSign's centralized platform for creating, managing, and deploying advanced AI/ML solutions to enhance customer journeys within the Docusign Agreement Cloud. As a Machine Learning Engineer, you'll support all aspects of the machine learning lifecycle, including the research platform, training and deployment pipelines, and labeling and serving infrastructure. You'll also partner with expert applied researchers specializing in areas like document understanding, natural language processing (NLP), and computer vision to prototype and productionize solutions for real business use cases at scale. This is an individual contributor role reporting to the Senior Manager, Machine Learning. Responsibility Collaborate with Applied Science, Product and other engineers across multiple offices and time zones to create and deliver new machine learning products and features on time Contribute to the development of AI infrastructure by building highly scalable gRPC-based services to enable offline and online machine learning pipelines, ensuring enterprise-grade security and reliability Develop systems to optimize and create AI-assisted data labeling processes while maintaining appropriate and thorough data governance and security standards Contribute to the development of scalable model training infrastructure to minimize the time it takes to deploy the candidate models to production Optimize model performance (including open source and licensed LLMs) in production leveraging best practices for CPU/GPU inference on NVIDIA Triton with TensorRT / ONNX Improve platform observability by implementing tools and required infrastructure to monitor and analyze the performance of deployed AI services #J-18808-Ljbffr

Search Infrastructure Engineer What you can expect We’re building the next-generation AI-native knowledge platform to help organizations access and retrieve internal knowledge using LLMs. Join a fast-moving engineering team to build scalable, secure, and intelligent Retrieval-Augmented Generation (RAG) infrastructure — powering enterprise search, AI assistants, and knowledge discovery. About the Team You’ll work with top engineers, designers, and product thinkers to define "AI-powered search" in the enterprise. As a core team member, you’ll work on real-time document pipelines, vector databases, and permission-aware retrieval, pushing the boundaries of large language model systems at scale. Responsibilities Design and implement a scalable RAG system for real-time Q&A across internal content (meetings, messages, documents, videos, etc.). Build ingestion and indexing pipelines for semi-structured data with permission-aware access control. Develop APIs and backend systems for querying, retrieval, and ranking. Collaborate with ML/NLP engineers to improve embedding models and search quality. Ensure system reliability, low latency, and scalability. Monitor performance and optimize for high-throughput workloads. What we’re looking for 4+ years experience in backend or distributed systems engineering Productivity mindset with effective use of AI tools Experience designing and operating large-scale data pipelines (message queues, vector stores, Elasticsearch, etc.) Proven ability to build highly available, multi-tenant backend services Experience with document-level permission modeling and secure data handling Familiarity with cloud-native tools like Docker, Kubernetes, AWS Experience with Go is a plus Experience integrating with SaaS platforms (Google Workspace, Microsoft 365, Slack, etc.) Salary Range or OTE: Minimum: $127,700 Maximum: $255,400 Compensation includes base salary, bonus, and equity, based on qualifications and experience. Location-based variations may apply. Application window is at least 5 days, with a potential closing date of 10/03/25. Ways of Working Our hybrid model combines office and remote work, as indicated in the role description. Benefits Our benefits support physical, mental, emotional, and financial health, work-life balance, and community involvement. Click Learn for details. About Us Zoom helps people stay connected and productive. We offer products like Zoom Contact Center, Zoom Phone, Zoom Events, and more. We foster a collaborative, growth-oriented environment. Our Commitment We promote fair hiring and support candidates requiring accommodations. If needed, submit an Accommodations Request Form . #J-18808-Ljbffr