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- Tasks: Join our team to develop AI tools for sustainability reporting and make a real impact.
- Company: Watershed, a leading enterprise sustainability platform with a mission-driven culture.
- Benefits: Competitive salary, inclusive environment, and opportunities for professional growth.
- Why this job: Be a technical leader in AI and help companies achieve their sustainability goals.
- Qualifications: Experience with LLMs, strong full-stack skills, and a passion for innovation.
- Other info: Work in a dynamic office environment in London with global team collaboration.
The predicted salary is between 30000 - 50000 £ per year.
We're looking for a software engineer specialising in AI to join our sustainability AI reporting team. You will be a technical leader in helping us build a world class AI tool for companies to manage and report on their progress in sustainability. 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. We are looking for this hire to be based in our HQ in London 4 days per week.
Responsibilities
- Prototype, develop and iterate on a new product area for Watershed, giving our customers powerful AI tools for information extraction and report generation.
- Productionize and launch core technologies to power AI features on top of a wealth of operational sustainability data.
- Collaborate with product and other AI engineering teams to set product and technical strategy.
- Keep up with developments and state-of-the-art in AI to determine what is relevant to Watershed.
Qualifications
- Experience building products using LLMs, embeddings and other ML technologies.
- Full lifecycle experience of building, deploying and monitoring products that leverage LLMs, embeddings or other ML technologies.
- Experience leading cross functional teams in an innovative fast moving environment.
- A strong foundational understanding of machine learning models and practice, including model evaluation and performance.
- Strong full-stack development skills.
- Must be willing to work from an office 4 days per week (except for remote roles).
About Watershed: Watershed 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, 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!
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.
software engineer specialising in AI in London employer: Watershed Technology, Inc.
Contact Detail:
Watershed Technology, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land software engineer specialising in AI in London
✨Tip Number 1
Network like a pro! Reach out to current employees at Watershed on LinkedIn or other platforms. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare for coding interviews by practising common algorithms and data structures. Use platforms like LeetCode or HackerRank to sharpen your coding chops before the big day.
✨Tip Number 3
Be ready to discuss your projects! Have a few examples of your work with LLMs and embeddings at the ready. Talk about challenges you faced and how you overcame them – it shows your problem-solving skills.
✨Tip Number 4
Don’t forget to follow up! After your interviews, send a quick thank-you note to express your appreciation. It keeps you fresh in their minds and shows your enthusiasm for the role.
We think you need these skills to ace software engineer specialising in AI in London
Some tips for your application 🫡
Show Off Your Skills: When you're writing your application, make sure to highlight your experience with LLMs and embeddings. We want to see how you've used these technologies in real projects, so don’t hold back on the details!
Tailor Your Application: Make your application stand out by tailoring it to our job description. Mention how your background aligns with our mission at Watershed and how you can contribute to building powerful AI tools for sustainability.
Be Authentic: We love seeing the real you! Don’t be afraid to share your interests and what drives you in the field of AI. A bit of personality goes a long way in making your application memorable.
Apply Through Our Website: For the best chance of getting noticed, make sure to apply through our website. It’s the easiest way for us to keep track of your application and get you into the process smoothly!
How to prepare for a job interview at Watershed Technology, Inc.
✨Know Your AI Stuff
Make sure you brush up on your knowledge of LLMs, embeddings, and other machine learning technologies. Be ready to discuss how you've used these in past projects, as well as any challenges you faced and how you overcame them.
✨Showcase Your Leadership Skills
Since the role involves leading cross-functional teams, prepare examples that highlight your leadership experience. Think about times when you guided a team through a project or made strategic decisions that impacted the outcome.
✨Understand Watershed's Mission
Familiarise yourself with Watershed’s sustainability goals and how AI plays a role in achieving them. This will not only show your interest in the company but also help you align your answers with their mission during the interview.
✨Prepare for Technical Questions
Expect a coding interview or technical questions related to full-stack development. Practice common algorithms and data structures, and be ready to explain your thought process clearly while solving problems.
