Coda started with an observation: In a world full of applications, why do documents and spreadsheets still run everything? And why haven't they been meaningfully updated in over 50 years? Coda is a new doc that's familiar and flexible like the documents you're used to, but comes with building blocks you can combine to create docs as powerful as apps. It's a big product with an even bigger mission. And we need your help to spread the word! We're backed by some of the Valley's leading venture capitalists, and have assembled a world-class team across offices in San Francisco, Mountain View, and Seattle, and remote employees all over the US. In fact, all our jobs are open in any location across the US. Here's a quick overview of what we do.

About the Role

As a ML engineer at Coda you will build products that use the latest AI technology to build applied solutions for users problems, some of which can be seen at coda.io/ai. You will use LLMs and train models to help users write content, find and summarize structured and unstructured data, and build custom applications from natural language prompts.

You'll work with a stellar team of passionate, experienced engineers and product managers who have been instrumental in building some of the most widely-used technology products globally - including YouTube, Google Drive/Docs, Google Travel/Shopping, Amazon AWS, Pinterest, and Microsoft Azure. You'll report to Coda's head of AI engineering.

In this role you will:

Build solutions and guide direction and prioritization of which problems to solve, which to tackle in house, which to use third party products for, and how to integrate this all in a way that creates value for our users
Partner with the product and other engineering teams to enhance Coda by bringing the magic of AI across all of its surfaces
Work in a collaborative environment across multiple geo-located offices (Seattle, San Francisco, and Mountain View). Like many of our engineers, you can also work remotely
Help ensure our customers have an excellent experience using Coda
Participate in the engineering teams' on-call rotations for customer support and live production issues during business hours

You may be a great fit for this role if:

You have 6+ years of industry experience in a software engineering role and have a software engineering degree or equivalent experience
You have spent 3+ years working with machine learning and have experience training and using large language models/natural language processing
You have experience with Python and a major ML framework (PyTorch, TensorFlow, etc.)
You have worked through model creation and serving end to end (data collection, training, evaluation, productionization)
You are motivated and excel when challenged

How we care for our Codans!

We are committed to providing highly competitive cash compensation, equity, and benefits. Check out our compensation philosophy. The compensation offered for this role will be based on multiple factors such as the role's scope and complexity, and the candidate's experience and expertise, and may vary from the range provided: $125,000 - $250,000.

Starting on your first day of employment, Coda offers a wide range of benefits and perks that support eligible employees and their family members. Some of our benefits include:

Medical, Dental, Vision and Life Insurance
401k
Optional Remote or in-office work
Commuter Benefits
Cell & Internet Subsidy
Lunch Subsidy
Fitness Subsidy
Parental Leave
Annual Educational Stipend

At Coda, we are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants. We do not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. Coda believes that diversity and inclusion among our teammates is critical to our success as a company, and we seek to recruit, develop and retain the most talented people from a diverse candidate pool.

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