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- Tasks: Lead and scale a new Machine Learning function, driving AI/ML strategy.
- Company: Join a fast-growing Series A climate data start-up backed by Google Ventures.
- Benefits: Enjoy a competitive salary, equity options, and flexible working arrangements.
- Why this job: Be at the forefront of climate risk innovation with a dynamic team and impactful projects.
- Qualifications: 5+ years in Python development, expertise in ML libraries, and leadership experience required.
- Other info: Opportunity to work with major global firms and contribute to GenAI initiatives.
The predicted salary is between 100000 - 140000 £ per year.
Director of AI/Machine Learning
Series A Climate Data/AI Start Up
£128,000 base + equity (3 days on site, Central London, 2 from home)
Lead and scale a brand new Machine Learning function at one of the UK\’s fastest scaling Series A start ups. With heavy investment from Google Ventures and Series B about to kick off early next year, this is a unique opportunity for a Lead ML Engineer who wants to take the next step in their career.
This firm partner with a range of the largest banks, insurance and real estate firms in the world. They have built out a series of AI driven products and tools that predict the P&L losses these firms will experience due to severe weather events in the future. They are on their way to take over the climate risk industry.
As ML Director you will work closely with senior stakeholders and product teams to drive the companies AI/ML strategy, remaining hands on, building out end to end GenAI features and ML models.
Must Have
- 5 + years in Python development, specializing in ML Libraries such as Scikit-learn and PyTorch.
- Proven ability to lead teams and work with non-technical stakeholders.
- Have worked on GenAI initiatives
Nice to have
- Experience in an early start up environment
- Experience working with Geo-spatial data
Director of Machine Learning employer: Stanford Black Limited
Contact Detail:
Stanford Black Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Director of Machine Learning
✨Tip Number 1
Network with professionals in the AI and machine learning space. Attend industry meetups, conferences, or webinars where you can connect with people who work at similar companies or have insights into the start-up culture.
✨Tip Number 2
Showcase your leadership skills by sharing examples of how you've successfully led teams in previous roles. Be prepared to discuss specific projects where you collaborated with non-technical stakeholders to achieve results.
✨Tip Number 3
Familiarise yourself with the latest trends in climate data and AI applications. Being knowledgeable about how these technologies are being used in the industry will help you stand out as a candidate who is genuinely interested in the company's mission.
✨Tip Number 4
Prepare to discuss your experience with GenAI initiatives in detail. Highlight any specific projects you've worked on that involved generative models, as this will be crucial for demonstrating your fit for the role.
We think you need these skills to ace Director of Machine Learning
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in Python development and machine learning libraries like Scikit-learn and PyTorch. Emphasise any leadership roles you've held and your ability to work with non-technical stakeholders.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company’s mission in the climate risk industry. Mention specific projects or achievements that demonstrate your expertise in GenAI and your experience in leading teams.
Showcase Relevant Experience: If you have experience in an early start-up environment or working with geo-spatial data, make sure to include this in your application. Highlight how these experiences have prepared you for the challenges of the Director of Machine Learning role.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any spelling or grammatical errors. A polished application reflects your attention to detail and professionalism.
How to prepare for a job interview at Stanford Black Limited
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with Python and ML libraries like Scikit-learn and PyTorch. Highlight specific projects where you've successfully implemented machine learning solutions, especially those related to GenAI.
✨Demonstrate Leadership Skills
Since the role involves leading a new Machine Learning function, be ready to share examples of how you've led teams in the past. Discuss your approach to managing both technical and non-technical stakeholders to ensure everyone is aligned.
✨Understand the Company's Mission
Research the start-up's focus on climate risk and their AI-driven products. Be prepared to discuss how your skills can contribute to their mission and how you can help scale their ML initiatives effectively.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Think about challenges you've faced in previous roles, particularly in early-stage environments, and how you overcame them.
