<h2>About Watershed</h2><a href="https://watershed.com/">Watershed</a> is the enterprise sustainability platform. Companies like Airbnb, Carlyle Group, FedEx, Visa, and Dr. Martens use Watershed to manage climate and ESG data, produce audit-ready metrics for voluntary and regulatory reporting including CSRD, and drive real decarbonization. We are looking for team members who love product-building, want to work hard at a mission-oriented startup, and will collaborate with us in shaping the culture of a growing team.We have offices in San Francisco, New York, Denver, London, Paris, Berlin, Sydney, Mexico City, and remote team members across the US and Europe. We hope that you'll be interested in joining us!<h2>The role</h2>We're looking for a seasoned machine learning engineer specializing in AI to join our team. You will be a technical leader in helping us build a world class AI tools for companies to measure and reduce their carbon emissions. You'll leverage LLMs, embeddings, and other AI technologies to deliver features to our customers, and help lay the technical foundations for AI at Watershed.In this role you will:<ul style=""><li>Prototype, develop and iterate on new product areas for Watershed, giving our customers powerful AI tools for transforming data and identifying ways to reduce their emissions</li><li>Productionize and launch core technologies to power AI features on top of a wealth of operational sustainability data</li><li>Collaborate with product and other AI engineering teams to set product and technical strategy</li><li>Build evals, fine tune, create agent harnesses to build reliable AI powered systems</li><li>Keep up with developments and state-of-the-art in AI to determine what is relevant to Watershed</li><li>Write performant, well-crafted, tested, and maintainable code across our technical stack</li></ul>You might be a good fit if you have:<ul style=""><li>8+ years of experience in Machine Learning / AI engineering</li><li>Experience building products using LLMs, embeddings and other ML technologies</li><li>Full lifecycle experience of building, deploying and monitoring products that leverage LLMs, embeddings or other ML technologies</li><li>Experience leading cross functional teams in an innovative fast moving environment</li><li>A strong foundational understanding of machine learning models and practice, including model evaluation and performance</li><li>Strong full-stack development skills</li></ul> Must be willing to work from an office 4 days per week (except for remote roles)Watershed has hub offices in San Francisco, New York, London, and Mexico City and satellite offices in Denver, Sydney, Paris, and Berlin. Where we have offices, employees are expected to be in office for 4 days per week. Certain jobs are open to being remote and will be specifically noted on the jobs page and in the job description if so.What’s the interview process like?It starts the same for every candidate: getting to know the team members through 1 to 2 conversations about Watershed, your experience, and your interests. Next steps can vary by role, but usual next steps are a skill or experience interview (e.g. a coding interview for an engineer, a portfolio review for a designer, deeper experience call for other roles) which leads to a virtual or in person interview panel. We prioritize transparency and lack of surprise throughout the process.What if I need accommodations for my interview?At Watershed, we are dedicated to ensuring an inclusive recruitment process. We provide reasonable accommodations for candidates with disabilities, long-term conditions, mental health needs, religious observances, neurodivergence, or pregnancy-related support requirements. If you need assistance during your process, please contact your recruiter.

Watershed is the enterprise sustainability platform. Companies like Airbnb, Carlyle Group, the CDP, YETI, and BBVA use Watershed to reduce emissions, meet customer, investor and regulatory requirements, and modernize their sustainability programs.With offices in London, New York and San Francisco, and remote employees across the US and Europe, we’re growing fast and hiring for a variety of roles! Explore all of our open opportunities at <a target="_blank" rel="noopener noreferrer nofollow" href="http://watershed.com/jobs">watershed.com/jobs</a>.Watershed’s advisors and investors include Mark Carney, Christiana Figueres, Al Gore, Sequoia, and Kleiner Perkins.

Staff machine learning engineer

<h2>About Watershed</h2><a href="https://watershed.com/">Watershed</a> is the enterprise sustainability platform. Companies like Airbnb, Carlyle Group, FedEx, Visa, and Dr. Martens use Watershed to manage climate and ESG data, produce audit-ready metrics for voluntary and regulatory reporting including CSRD, and drive real decarbonization. We are looking for team members who love product-building, want to work hard at a mission-oriented startup, and will collaborate with us in shaping the culture of a growing team.We have offices in San Francisco, New York, Denver, London, Paris, Berlin, Sydney, Mexico City, and remote team members across the US and Europe. We hope that you'll be interested in joining us!<h2>The role</h2>We're looking for a seasoned machine learning engineer specializing in AI to join our team. You will be a technical leader in helping us build a world class AI tools for companies to measure and reduce their carbon emissions. You'll leverage LLMs, embeddings, and other AI technologies to deliver features to our customers, and help lay the technical foundations for AI at Watershed.In this role you will:<ul><li>Prototype, develop and iterate on new product areas for Watershed, giving our customers powerful AI tools for transforming data and identifying ways to reduce their emissions</li><li>Productionize and launch core technologies to power AI features on top of a wealth of operational sustainability data</li><li>Collaborate with product and other AI engineering teams to set product and technical strategy</li><li>Build evals, fine tune, create agent harnesses to build reliable AI powered systems</li><li>Keep up with developments and state-of-the-art in AI to determine what is relevant to Watershed</li><li>Write performant, well-crafted, tested, and maintainable code across our technical stack</li></ul>You might be a good fit if you have:<ul><li>8+ years of experience in Machine Learning / AI engineering</li><li>Experience building products using LLMs, embeddings and other ML technologies</li><li>Full lifecycle experience of building, deploying and monitoring products that leverage LLMs, embeddings or other ML technologies</li><li>Experience leading cross functional teams in an innovative fast moving environment</li><li>A strong foundational understanding of machine learning models and practice, including model evaluation and performance</li><li>Strong full-stack development skills</li></ul> Must be willing to work from an office 4 days per week (except for remote roles)Watershed has hub offices in San Francisco, New York, London, and Mexico City and satellite offices in Denver, Sydney, Paris, and Berlin. Where we have offices, employees are expected to be in office for 4 days per week. Certain jobs are open to being remote and will be specifically noted on the jobs page and in the job description if so.What’s the interview process like?It starts the same for every candidate: getting to know the team members through 1 to 2 conversations about Watershed, your experience, and your interests. Next steps can vary by role, but usual next steps are a skill or experience interview (e.g. a coding interview for an engineer, a portfolio review for a designer, deeper experience call for other roles) which leads to a virtual or in person interview panel. We prioritize transparency and lack of surprise throughout the process.What if I need accommodations for my interview?At Watershed, we are dedicated to ensuring an inclusive recruitment process. We provide reasonable accommodations for candidates with disabilities, long-term conditions, mental health needs, religious observances, neurodivergence, or pregnancy-related support requirements. If you need assistance during your process, please contact your recruiter.

Staff machine learning engineer

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