Clarifai is a leading, full-lifecycle deep learning AI platform for computer vision, natural language processing, and audio recognition. We help organizations transform unstructured images, video, text, and audio data into structured data at a significantly faster and more accurate rate than humans would be able to do on their own. Founded in 2013 by Matt Zeiler, Ph.D. Clarifai has been a market leader in AI since winning the top five places in image classification at the 2013 ImageNet Challenge. Clarifai continues to grow with employees remotely based throughout the United States and in Tallinn, Estonia.

We have raised $100M in funding to date, with $60M coming from our most recent Series C, and are backed by industry leaders like Menlo Ventures, Union Square Ventures, Lux Capital, New Enterprise Associates, LDV Capital, Corazon Capital, Google Ventures, NVIDIA, Qualcomm and Osage.

Clarifai is proud to be an equal opportunity workplace dedicated to pursuing, hiring, and retaining a diverse workforce.

You will be responsible for the development of custom models to solve real world problems for business and expand Clarifai's presence in the rapidly expanding AI solutions space.&nbsp;

Clarifai is a leading, full-lifecycle deep learning AI platform for computer vision, natural language processing, and audio recognition

Data Scientist

Etsy is the global marketplace for unique and creative goods. We build, power, and evolve the tools and technologies that connect entrepreneurs with buyers around the world. Etsy, Inc.'s 'house of brands' portfolio has expanded to now include four individually distinct ecommerce brands -- Etsy, fashion resale marketplace Depop, musical instrument marketplace Reverb, and Brazil-based handmade goods marketplace Elo7. As an Etsy employee, you'll tackle unique problems alongside talented coworkers committed to Keeping Commerce Human. We're large enough that you'll focus on meaningful, complex challenges, but small enough that you can make a rewarding impact.

Etsy is hiring a Machine Learning Engineer to join the Retrieval Sciences team. We are looking for individuals who are product and delivery-driven, and are passionate about making ML innovations in information retrieval to help improve the Etsy buyer/seller experience.

Does the problem of finding a needle in the haystack—the perfect handmade or vintage product among hundreds of millions that is unique for each use—using the latest ML innovations, at scale in a two-sided marketplace with 105+ million buyers, 5+ million sellers sound exciting to you? If so, this could be the perfect match.

Our team works closely with other Machine Learning and Information Retrieval Platform teams to develop state of the art, large-scale models to retrieve the most relevant products for Etsy buyers. We are looking for individuals who are passionate about making ML innovations in search and retrieval to improve the Etsy buyer experience.

This is a full-time role based in Brooklyn, NY, or San Francisco, CA, or remote within the US &amp; Canada. Etsy offers three different work modes to meet the variety of needs and preferences of our team: Flex mode for candidates who are comfortable traveling to an office location at least 4-6 days per month, Remote mode, and Office-based mode. Learn more about our flexible work modes and vaccination policy&nbsp;<a href="https://careers.etsy.com/global/en/how-and-where-we-work">here</a>.

Our team builds the first stage candidate retrieval layer that powers multiple applications in Etsy, including search at etsy.com. We closely track the latest techniques in ML, NLP, and IR research and apply them at Etsy’s scale of hundreds of millions of hand-crafted and vintage items. Here is a sample of models and techniques we design, build, and productionize:

If you're interested in joining the team at Etsy, please send a cover letter and resume telling us why you'd be right for the position. As you've hopefully seen already, Etsy is a place that values individuality and variety. We don't want you to be like everyone else -- we want you to be like you! So write to us and tell us what you're all about.

At Etsy, we believe that a diverse, equitable and inclusive workplace makes us a more relevant, more competitive, and more resilient company. We encourage people from all backgrounds, ages, abilities, and experiences to apply. Etsy is an equal opportunity employer. We do not discriminate on the basis of race, color, ancestry, religion, national origin, sexual orientation, age, citizenship, marital or family status, disability, gender, gender identity or expression, pregnancy or caregiver status, veteran status, or any other legally protected status. We will ensure that individuals with disabilities are provided reasonable accommodations to participate in the job application and interview process, to perform essential job functions, and to receive other benefits and privileges of employment. While Etsy supports visa sponsorship, sponsorship opportunities may be limited to certain roles and skillsets.

Many Etsy roles are open to remote candidates, and you'll be able to identify which ones within the location header of each job description. We're open to remote hires from all U.S. states except Hawaii and Alaska. For candidates who will work remotely from Colorado, visit this&nbsp;<a href="https://careers.etsy.com/global/en/Colorado-Equal-Pay-for-Equal-Work-Act-Information">link</a>&nbsp;for information related to Colorado's Equal Pay for Equal Work Act.

Etsy is the global marketplace for unique and creative goods.

Software Engineer II, Machine Learning, Retrieval Sciences

Cash App is the fastest growing financial brand in the world. Built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic money app with over 36&nbsp;million active monthly users.&nbsp;

Loved by customers and by pop culture, we’ve held the #1 spot in finance on the App Store for almost two years, and our social media posts see more engagement in a day than most financial brands see in a year.&nbsp;

With major offices in San Francisco, New York, St. Louis, Portland, Kitchener-Waterloo, Toronto and Melbourne, Cash App is bringing a better way to send, spend, and save to anyone who has ever sought an alternative to today’s banking system.

Machine Learning at Cash App has swiftly grown to become a central function of the business, with over 100 people working on solving some of the most cutting edge ML questions in FinTech. Our team is continuing to grow and we’re looking for Engineers with experience developing ML pipelines and infrastructure to join us and build out the next generation platform to power use cases across the company. Across the team, we employ methods ranging from simple heuristics to Deep Learning technology to improve our performance and services. We’re also excited to explore new directions with the team to continue pushing the boundaries of what’s possible.

Our ML Engineers operate embedded in product-focused Workstreams and work in close collaboration with Data Scientists, ML Modelers and Software Engineers from across Cash App. Here are some Workstreams that are currently growing:

The ML Identity team focuses on providing AI-based opportunities to establish and verify Cash App's customer identities across the services we provide. This team works to build out both security and accessibility for Cash App users. We're a small team of engineers focused on exploring AI longshots, balancing a passion for advancing what's possible with a commitment to positive real-world impact. The ML Identity engineering team is led by&nbsp;<a href="https://www.linkedin.com/in/kyledef">Kyle</a>&nbsp;(who you'll report to) and this is a chance to work with us as a founding member.

The Risk team applies ML to protect our customers and our company’s bottom line from an ever changing landscape of fraud and platform abuse. We are continually refining and searching for new ways to leverage ML to stay ahead of ever more sophisticated fraud and scam patterns. In addition, we are continually evolving our platform to scale up in line with Cash App’s global expansion, and to provide the rapid payments platform that our customers expect and demand.

The Banking ML team focuses on all things ML related to the Cash Card and Banking at Cash. There is an element of risk and fraud prevention involved. From building pipelines and models to combat fraud on every Cash Card transaction and activation, to building out data models and pipelines to enable a large expansion of Cash Check Deposits. We are a new team that was created to support the fast growing banking space within Cash App. Our ultimate goal is to ensure that our customers experience safe and reliable Banking with Cash App.

The Cash Customer Support ML team has a vision to provide customer support that’s better than humans through ML. We’re a mixed team of engineers and modellers that work together to deliver models that help us support our customers when they run into problems. We currently use ML automation on two support channels: email and in-app chat. We’re actively working towards making these perform better and we’re always looking for innovative solutions to help our customers with ML.

Stack:&nbsp; We value general engineering skill and versatility over existing domain knowledge, but here’s a sample of what we currently use:

We’re working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Square is a proud equal opportunity employer. We work hard to evaluate all employees and job applicants consistently, without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.&nbsp;

We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible.

Additionally, we consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.

Square, Inc. (NYSE: SQ) builds tools to empower businesses and individuals to participate in the economy. Sellers use Square to reach buyers online and in person, manage their business, and access financing. Individuals use Cash App to spend, send, store, and invest money. And TIDAL is a global music and entertainment platform that expands Square's purpose of economic empowerment to artists. Square, Inc. has offices in the United States, Canada, Japan, Australia, Ireland, Spain, Norway, and the UK.

Our team is continuing to grow and we’re looking for Engineers with experience developing ML pipelines and infrastructure to join us and build out the next generation platform to power use cases across the company. 

Machine Learning Engineer

Want to infuse a $25B sector of the insurance and real estate industry with predictive analytics and a tech-forward customer experience? Yearning for a startup culture within a profitable nationwide company? Join&nbsp;Doma&nbsp;and send an entirely new type&nbsp;of real estate model into the wild.&nbsp;

Doma and its family of brands - States Title, North American Title Company (NATC) and North American Title Insurance Company (NATIC) - offer solutions for lenders, real estate professionals, title agents, and homeowners that make closings vastly more simple and efficient, reducing cost and increasing customer satisfaction.&nbsp;

The data science team at Doma is building revolutionary workflow automation using Natural Language Understanding. We are applying state of the art NLP techniques in an applied setting, and you will have an opportunity to experiment, innovate, and unlock novel solutions within our industry. You will be empowered to influence the direction of NLP solutions at the company, and have your work published and patented.

We're proud of the sophisticated data ingestion process we have built, as well as the multi-model ecosystem that is already live. We have high expectations of communication, accountability, and mathematical rigor, and are looking for those who would be inspired and stimulated in such an environment.

What we’re looking for in a candidate:&nbsp;

We want the work you do here to be the best work of your life.&nbsp;&nbsp;

We believe the most valuable investment we can make - and the greatest boost we can give to your career - is to build an outstanding team of colleagues who are passionate about our mission.&nbsp;

We currently offer the following benefits and will continually evolve them with the goal of efficiently attracting, retaining, and leveraging the very highest quality talent.&nbsp;

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.&nbsp;

Build the solution that transforms the real estate industry! 

Senior Machine Learning Engineer- Deep Learning

Grammarly offers a remote-first hybrid working model. Team members can work primarily remotely. Starting in 2022, teams will meet in person a few weeks every quarter in one of Grammarly's hubs, currently in San Francisco, Vancouver, New York, and Kyiv. To ensure that teams are able to overlap in their working hours and to meet face-to-face when needed, all team members need to live within three time zones of a hub.&nbsp;<a href="http://www.grammarly.com/blog/remote-first-hybrid-work-model">Read more about our remote-first hybrid model.</a>

Grammarly team members who will be collaborating at our San Francisco hub must be based in the United States.

Grammarly empowers people to thrive and connect, whenever and wherever they communicate. More than 30 million people and 30,000 teams around the world use our AI-powered writing assistant every day. All of this begins with our team collaborating in a values-driven and learning-oriented environment.

To achieve our ambitious goals, we’re looking for a Software Engineer focused on machine learning to join our team. This individual will be responsible for building end-to-end intelligence systems that solve complex user problems, including applying ML to solve new problems as well as building the infrastructure and systems that will enable this to operate effectively at scale. The role will have the opportunity to provide feedback about the systems and tools in place to facilitate the creation and improvement of a machine learning platform that can increase the efficacy of the engineering team.

Grammarly’s engineers and researchers have the freedom to innovate and uncover breakthroughs—and, in turn, influence our product roadmap. The complexity of our technical challenges is growing rapidly as we scale our interfaces, algorithms, and infrastructure. Read more about&nbsp;<a href="https://www.grammarly.com/jobs/engineering">our stack</a>&nbsp;or hear from our team on our&nbsp;<a href="https://medium.com/@Grammarly">technical blog</a>.

The Software Engineer for machine learning will need to stay up-to-date on the quickly evolving field of NLP while also focusing on building production systems. The majority of the problems we’re tackling haven't already been solved elsewhere, which provides the opportunity for creativity and innovative problem-solving.&nbsp;

Working on the Machine Learning team requires close partnership with analytical linguists, computational linguists, and research scientists. You will have the chance to deepen your skills in machine learning and deep learning while increasing breadth in related areas to up-level our entire team.&nbsp;

Support for you, professionally and personally

At Grammarly, we value our differences, and we encourage all—especially those whose identities are traditionally underrepresented in tech organizations—to apply. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law. Grammarly will consider qualified applicants with criminal histories in a manner consistent with the San Francisco Fair Chance Ordinance. Grammarly is an equal opportunity employer and participant in the U.S. Federal E-Verify program.

Grammarly empowers people to thrive and connect, whenever and wherever they communicate

Software Engineer, Machine Learning

We are looking for a Senior Machine Learning Engineer with experience in Natural Language Processing who combines technical, communication, and analytical capabilities; who can architect and implement efficient algorithms in tensorflow; and who will have the opportunity to design and develop creative, compelling, and cutting-edge systems that support our mission.

We don’t draw a hard line between our research and engineering teams, we all work on the same stack and share work, knowledge, and tools. Your work will be used by thousands of developers all over the world, and you’ll spend time with our community to get inspiration and feedback. We’re not here to chase SotA on established benchmarks. To ship machine learning products that really help our community, you’ll need to develop new machine learning tools that help developers build great conversational software, and enable them to build things that they can’t currently. You'll have to come up with good architectural designs, quality code, and break an ambitious long-term vision down into milestones and issues. For example, you should feel comfortable refactoring&nbsp;<a href="https://github.com/RasaHQ/rasa/blob/master/rasa/utils/tensorflow/transformer.py">this code</a>&nbsp;to accommodate different types of attention.

We do fundamental research, and we ship commercial quality software that puts it to use. Because engineering is so close to research, you’ll quickly learn a lot about research practice and translating it into working systems. You can check out some of our projects on our<a href="https://rasa.com/research">&nbsp;research page</a>.

Please keep in mind that we are describing the background we imagine would best fit the role. Even if you don’t meet all the requirements, yet you are confident that you are up for the task, we absolutely want to get to know you!

We’re a startup, so you’ll have to be comfortable rolling up your sleeves and doing whatever is required to support our mission. However, you can definitely expect to:

Rasa supplies the standard infrastructure for conversational AI, providing the tools required to build better, more resilient contextual assistants. With more than 10 million downloads since launch, Rasa Open Source is loved by developers worldwide, with a friendly, fast-growing community learning from each other and working together to make better text- and voice-based AI assistants.

Rasa offers three key products in its suite of conversational AI offering. Rasa Open Source is the most popular open source software in conversational AI. Rasa X, released in 2019, is a free toolset that helps developers quickly improve and share an AI assistant built with Rasa Open Source. Rasa Enterprise is the company's commercial offering, providing an enterprise-grade platform for developing contextual assistants at scale. Rasa runs in production everywhere from startups to Fortune 500s, and provides the data privacy and security needed to enterprises of every size.

Rasa is privately held, with funding from Accel, Andreessen Horowitz, Basis Set Ventures, and others. The company was founded in 2016 and has offices in Berlin, Germany and Edinburgh, United Kingdom.Rasa is an equal opportunity employer. We are still a small team and are committed to growing in an inclusive manner. We want to augment our team with talented, compassionate people irrespective of race, color, religion, national origin, sex, physical or mental disability, or age.

We’re looking for a motivated machine learning engineer to join us at Rasa. The position offers the opportunity to have a huge impact at an early stage startup.

Senior Software Engineer — Machine Learning

As a Senior Python Engineer (m/f/x) you will work on making neural search scalable and accessible for enterprises all around the world. You will improve our open-source python framework Haystack to make it more developer-friendly, extend it's functionality and improve the scalability.You will join us in building &amp; shaping "Haystack Hub" a cloud-based SaaS product to facilitate neural search for our enterprise clients.Examples: Integrate a FAISS backend in Haystack; Efficient distribution of requests in the REST API across workers; Interact with our GitHub Community to implement a feature request

Natural Language Processing Jobs in RemoteOctober - 2022

Find Jobs

Location

Industry & Specialization

Featured Company

Get Job Alert

Data Scientistat Clarifai

Clarifai is a leading, full-lifecycle deep learning AI platform for computer vision, natural language processing, and audio recognition

Software Engineer II, Machine Learning, Retrieval Sciencesat Etsy

Etsy is the global marketplace for unique and creative goods.

Machine Learning Engineerat Square

Our team is continuing to grow and we’re looking for Engineers with experience developing ML pipelines and infrastructure to join us and build out the next generation platform to power use cases across the company.

Senior Machine Learning Engineer- Deep Learningat Doma

Build the solution that transforms the real estate industry!

Software Engineer, Machine Learningat Grammarly

Grammarly empowers people to thrive and connect, whenever and wherever they communicate

Senior Software Engineer — Machine Learningat RASA

We’re looking for a motivated machine learning engineer to join us at Rasa. The position offers the opportunity to have a huge impact at an early stage startup.

(Senior) Software Engineer (f/m/x)at deepset

As a Senior Python Engineer (m/f/x) you will work on making neural search scalable and accessible for enterprises all around the world.