494 Machine Learning jobs in Washington

The data engineering team at this entertainment/media company is looking to add a resource to help design and develop machine learning models to assist finance and product teams for improved quarterly spend forecasting. This person will be developing scalable and efficient data pipelines and processes for training, inferencing and model evaluation for high accuracy. You will be collaborating with engineering teams, finance and product managers in an open, and creative environment.

Additionally will work closely with Frontend engineers and Software Engineers to present forecasts in a performant and timely manner.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to com.

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* 4+ years of working experience on machine learning, and statistics with focus on forecasting in leading product companies.

* Proficient with Python, Spark, Databricks, SQL,

* Large scale ML/DL platforms and ML forecasting models

* Writing ML pipelines and doing ML notebooks and ML flows

* Passion for technology, open to interdisciplinary work, and experience in building data-driven services and applications.

* MS in Math, computer science or AI related field

* Understanding of generative machine learning models, including architectures like transformers and popular implementations such as GPT

Understand different genAI application development methods.

Join to apply for the Machine Learning Engineer role at ElastixAI Join to apply for the Machine Learning Engineer role at ElastixAI Get AI-powered advice on this job and more exclusive features. Location: Seattle, WA (Hybrid - 3 days/week in office) About ElastixAI: ElastixAI is an early-stage startup poised to revolutionize AI inference infrastructure. We are developing a cutting-edge AI inference solution that dramatically improves efficiency. Our solution is going to dynamically adapt to any deployment, constantly evolving to power the next generation AI use cases. Role Summary: We are looking for a talented Machine Learning Engineer to play a key role in building our core AI inference platform. You will be responsible for designing and developing critical components, including ML model deployment, innovative model optimization pipelines, and performance benchmarking and simulation workflows. This is a highly interdisciplinary role where you'll collaborate closely with our multi-disciplinary team to ensure our entire stack works in harmony to deliver optimal AI inference solutions. Key Responsibilities: Design, develop, and maintain core components of our ML platform, focusing on scalability, reliability, and ease of use. Research, prototype, and implement advanced ML techniques to optimize inference performance across diverse hardware targets. Collaborate with systems and cloud engineers to ensure efficient utilization of underlying hardware resources. Contribute to the design of APIs and tools that enable seamless integration and management of our inference solutions. Required Qualifications: PhD/MS in Computer Science, Computer Engineering, or a related field. 3+ years of machine learning R&D and deployment experience. Strong proficiency in one or more programming languages such as Python, or C++. Proficiency in at least one ML framework (e.g., PyTorch, TensorFlow, JAX). Solid understanding of software engineering best practices, including data structures, algorithms, and testing. Excellent problem-solving abilities and a knack for tackling complex technical challenges. Strong communication skills and a proven ability to collaborate effectively in a cross-functional team environment. Ability to thrive in a fast-paced, dynamic startup environment. Preferred/Bonus Qualifications: Experience with training generative machine learning models. Experience with optimizing the performance of machine learning models. Experience leading research initiatives in Machine Learning, Natural Language Processing, and related fields. Familiarity with performance analysis, profiling, and optimization techniques. Experience with cloud platforms (AWS, GCP, Azure). Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes). What We Offer: A chance to be a foundational engineer in an innovative AI startup. A dynamic and collaborative work environment and the change to have a significant impact on new technology The opportunity to work on challenging problems at the intersection of ML, software, and systems. Competitive compensation and startup equity package Comprehensive medical, dental, and vision coverage (100% paid by employer) Flexible Time Off (FTO) Paid parental leave Gym or fitness benefit Investment in employee learning & development Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job function Job function Engineering and Information Technology Industries Software Development Referrals increase your chances of interviewing at ElastixAI by 2x Get notified about new Machine Learning Engineer jobs in Seattle, WA . Seattle, WA $99,500.00-$87,000.00 2 weeks ago Software Engineer, Machine Learning (Multiple Levels) - Slack Seattle, WA 167,300.00- 334,600.00 1 day ago Software Engineer, Machine Learning (Multiple Levels) - Slack Bellevue, WA 167,300.00- 334,600.00 1 day ago Bellevue, WA 130,000.00- 200,000.00 12 hours ago Software Developer-Artificial Intelligent/Machine Learning Seattle, WA 100,000.00- 220,000.00 4 months ago Software Engineer - Security, Multiple Locations Redmond, WA 81,900.00- 174,600.00 1 week ago Bellevue, WA 130,000.00- 170,000.00 1 week ago Seattle, WA 94,000.00- 120,000.00 4 days ago Seattle, WA 127,000.00- 240,000.00 1 week ago Redmond, WA 30,000.00- 215,400.00 1 week ago Seattle, WA 118,657.00- 168,150.00 4 days ago Machine Learning Engineer, Identity Product Seattle, WA 212,000.00- 318,000.00 3 weeks ago Data Scientist – AI/ML Recommendations & Personalization Redmond, WA $1 0,600.00- 215,400.00 1 day ago Senior ML Engineer, Applied Machine Learning Machine Learning Engineer Graduate (Search E-Commerce - Seattle) - 2025 Start (BS/MS) Seattle, WA 118,657.00- 168,150.00 2 weeks ago Machine Learning Engineer, Computer Vision Machine Learning Engineer, Forecast Platform Software Engineer, Semantic Normalization - Fullstack (Entry-Level) Greater Seattle Area 75,000.00- 90,000.00 1 week ago Kirkland, WA 141,000.00- 202,000.00 2 weeks ago Machine Learning Engineer Graduate (TikTok E-Commerce - Conversational AI) -2025 Start (BS/MS) Seattle, WA 104,500.00- 139,650.00 2 days ago Sr. Software Development Engineer in Test (SDET) - Infotainment Machine Learning Engineer Graduate Data-Search - TikTok.US - San Jose) - 2025 Start (BS/MS) Seattle, WA 106,400.00- 168,150.00 4 days ago Data Scientist, Energy Analytics, Google Cloud Seattle, WA 166,000.00- 244,000.00 1 day ago We’re unlocking community knowledge in a new way. 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About Hive Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive’s solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more. Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI! Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the forefront of deep learning technology, prototyping state-of-the-art neural net models and launching these models into production. We value hard workers who have no qualms working with terabyte-scale datasets, who are interested in learning new technologies at all levels of the machine learning stack, and who move fast and take ownership of their projects. Our ideal candidate has experience creating a working machine learning-powered project from the ground up, contributes innovative ideas and ingenious implementations to the team, and is capable of planning out scalable, maintainable data pipelines. Responsibilities Everything involved in applying a ML model to a production use case, including, designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed Interface closely with the Backend and DevOps teams as well as with our internal data labeling services Utilize OWASP top 10 techniques to secure code from vulnerabilities Maintain awareness of industry best practices for data maintenance handling as it relates to your role Adhere to policies, guidelines and procedures pertaining to the protection of information assets Report actual or suspected security and/or policy violations/breaches to an appropriate authority Requirements You have an undergraduate or graduate degree in computer science or similar technical field, with significant coursework in mathematics or statistics You have 1-2 years industry machine learning experience You have successfully trained and deployed a deep learning machine model (image, NLP, video, or audio) into production, with measurably improved performance over baseline, either in industry or as a personal project You have strong experience with a high-level machine learning frameworks such as Tensorflow, Caffe, or Torch, and familiarity with the others You know the ins and outs of Python, especially as it applies to the above ML frameworks You are capable of quickly coding and prototyping data pipelines involving any combination of Python, Node, bash, and linux command-line tools, especially when applied to large datasets consisting of millions of files You have a working knowledge of the following technologies, or are not afraid of picking it up on the fly: C++, Scala/Spark, SQL, Cassandra, Docker You are up-to-date on the latest deep neural net research and architectures, both in understanding the theory and motivations behind the techniques, as well as how to implement them in the ML framework of your choice You have great communication skills and ability to work with others You are a strong team player, with a do-whatever-it-takes attitude Who We Are We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Hive, you will have a steep learning curve and an opportunity to contribute to one of the fastest growing AI start-ups in San Francisco. The work you do here will have a noticeable and direct impact on the development of the company. Thank you for your interest in Hive and we hope to meet you soon! The current expected base salary for this position ranges from $20,000 - 180,000. Actual compensation may vary depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the total compensation package that is provided to compensate and recognize employees for their work; stock options may be offered in addition to the range provided here. Employees are eligible to participate in a number of Company-sponsored benefits, including health, vision and dental insurance. Employees are also eligible to participate in a gym membership as part of our commitment to employee wellness. In addition, employees will be entitled to paid vacation in accordance with the Company's vacation policy. Hired applicant may receive an equity grant in the form of an option to purchase stock in the future for a specified price. #J-18808-Ljbffr

At IUNU (“you knew’), we’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 a Machine Learning Engineer for our AI team to develop products for our clients and the greenhouse industry. Machine Learning Engineer Responsibilities: Study and transform data science prototypes Design machine learning systems Research and implement appropriate ML algorithms and tools Develop machine learning applications according to requirements Select appropriate datasets and data representation methods Run machine learning tests and experiments Perform statistical analysis and fine-tuning using test results Train and retrain systems when necessary Extend existing ML libraries and frameworks Keep abreast of developments in the field Requirements: 3-5 years of proven experience as a Machine Learning Engineer or a similar role Strong experience with Deep Learning Understanding of data structures, data modeling, and software architecture Deep knowledge of math, probability, statistics, and algorithms Ability to write robust code in Python, Java, and R Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn) Excellent communication skills Ability to work in a team Outstanding analytical and problem-solving skills BSc in Computer Science, Mathematics, or a similar field; a Master’s degree is a plus Benefits: Comprehensive benefits, including healthcare and generous paid leave Opportunities for career growth within a fast-growing and innovative company Competitive Paid Time Off (PTO) policy Seniority Level: Mid-Senior level Employment Type: Full-time Job Function: Engineering and Information Technology Industries: Internet Publishing #J-18808-Ljbffr

Factspan is a pure play analytics company. We partner with you to build an analytics center of excellence, generating insights and solutions from your data to solve business challenges, make strategic recommendations and implement new processes that help you succeed. With offices in Seattle, USA and Bangalore, India; we use a global delivery model to service our clients. Our clients include Fortune 500 companies in Retail, Financial Services, Hospitality and Technology sectors. Job Description Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct end-to-end analysis that includes data gathering from various data storage platforms and requirements specification, processing, analysis, ongoing deliverables, and presentations. Hands on expertise in Machine Learning models using R/Python, SQL, well versed in statistical methodology including deep expertise and experience with statistical data analysi Requires a diversified technical person who can setup environments on AWS and integrate different pieces of solution. Develop data pipelines to integrate different data sources Experienced in using Google, Amazon NLP APIs to parse data and analyse output Experienced in using Amazon dockers to develop and deploy the solution Proficient in JAVA & Python programming Understanding of topic modelling, supervised & unsupervised machine learning Plan the project milestones, resourcing and work distribution Execute project in a timely manager, analyse risks and mitigate them Able to lead a technical team of data scientist and engineers Communicate the project progress, challenges, results and next action items to stake holders Qualifications 3-8 years of experience Bachelor’s/Master’s Degree in Engineering, Statistics, Mathematics Excellent hands-on working knowledge in R, Python, advanced predictive modelling, SQL, AWS Additional Information All your information will be kept confidential according to EEO guidelines. #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