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- Tasks: Lead and scale a new Machine Learning function, building GenAI features and ML models.
- 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, making a real-world impact.
- Qualifications: 5+ years in Python development with expertise in ML libraries like Scikit-learn and PyTorch.
- Other info: Opportunity to work closely with top banks and insurance firms globally.
The predicted salary is between 72000 - 84000 £ per year.
Lead AI/Machine Learning
Series A Climate Data/AI Start Up
£120,000 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, or senior 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 Lead AI/ML Engineer 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
Lead Machine Learning Engineer employer: Stanford Black Limited
Contact Detail:
Stanford Black Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Machine Learning Engineer
✨Tip Number 1
Network with professionals in the AI and machine learning space, especially those who have experience in start-ups. Attend industry meetups or conferences where you can connect with potential colleagues or even the hiring team.
✨Tip Number 2
Showcase your leadership skills by discussing any previous experiences where you've led a team or project. Be prepared to share specific examples of how you managed stakeholders and drove successful outcomes.
✨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 finance and insurance sectors will give you an edge during discussions.
✨Tip Number 4
Prepare to discuss your hands-on experience with Python and ML libraries like Scikit-learn and PyTorch. Be ready to explain your approach to building end-to-end GenAI features and how you’ve tackled challenges in previous projects.
We think you need these skills to ace Lead Machine Learning Engineer
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 climate risk. Mention specific projects or experiences that demonstrate your expertise in GenAI and your ability to lead a team.
Showcase Relevant Projects: If you have worked on relevant projects, especially those involving geo-spatial data or AI-driven products, be sure to include them in your application. This will help illustrate your hands-on experience and technical skills.
Highlight Your Start-Up Experience: If you have experience in an early start-up environment, make it clear in your application. Discuss how this experience has prepared you for the fast-paced and dynamic nature of the role at this Series A start-up.
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. Bring examples of projects where you've successfully implemented machine learning models, especially in GenAI initiatives.
✨Demonstrate Leadership Skills
Since the role involves leading a team, be ready to share specific instances where you've led projects or teams. Highlight how you managed non-technical stakeholders and ensured effective communication.
✨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 machine learning function.
✨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.
