We need an evangelist to connect our work to the world. Leap’s tech and approach to model evaluation is novel and little understood by domain experts, much less general ML practitioners. If you like to dive deep on new technology, read arXiv papers, and share your discoveries with the ML community this may be the role for you.

Total Cash Compensation: $110-150k/year

What to expect

You will act as the face of the company to the ML community. This includes both ML-native practitioners in the trenches of model development and research, and business users seeking to utilise ML. Your time will be split between content creation (lots of writing!), staying up-to-date on Leap’s product and research initiatives, and community engagement. Technical expertise is required, but this is primarily a relationship building and communications role.

The Ideal Candidate

Has experience in:

• ML Development: Possess a strong understanding of machine learning concepts and technologies, enabling you to speak confidently to developers and business users about ML interpretability, development, and evaluation.
• Effective Storytelling: Ability to weave engaging narratives around technical content, using real-world examples to captivate and educate your audience. You grasp novel complex concepts, understand how they fit into existing concepts and solutions, and explain them in a relatable way.
• Building Feedback Loops: Act as a bridge between the developer community, our product development and research teams, gathering feedback, feature requests, and insights to drive product improvements and research.
• Content Creation: Produce high-quality technical content, blog posts, tutorials, documentation, and videos, to educate and engage developers about our products, solutions, and research.
• Community Engagement: Build and maintain relationships with ML practitioners and orgs through in-person events, online communities, forums, social media, and other relevant platforms.
• Training and Workshops: Organize and conduct workshops, webinars, and training sessions to educate developers on how to effectively use our ML interpretability tools.
• Demos and Presentations: Deliver product demonstrations and presentations at conferences, meetups, and other events to showcase the capabilities and benefits of our solutions.
• Collaboration: Collaborate with internal teams, including research, product, and marketing to align developer outreach efforts with company goals.

Shares our values:

• Learning Mindset: A thirst for knowledge and a commitment to continuous learning. Eagerness to expand skill set, staying abreast of emerging technologies and industry best practices. There are no dumb questions.
• Resilience: The ability to adapt and thrive in a fast-paced and ever-changing environment in the face of challenges, setbacks, and tight deadlines, consistently finding solutions and persevering to achieve goals.
• Drive: Self-motivated with a strong desire to excel and exceed expectations, evident in the ability to take ownership of projects, and remain dedicated to delivering impactful solutions.
• Teamwork: The ability to work well with cross-functional teams and understand the importance of sharing knowledge, ideas, and responsibilities. A culture of collaboration, respect, and support.
• Customer-obsessed: Focus on delivering products that meet customer needs and expectations. Prioritising the user experience, actively seeking feedback and incorporating it into product development.