Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead the development of ML-driven solutions for climate and biodiversity action.
- Company: Join a remote-first startup focused on nature-based solutions and environmental impact.
- Benefits: Enjoy flexible hours, 32 days paid holiday, and mental wellbeing support.
- Why this job: Make a real-world impact while working in a supportive, growth-oriented culture.
- Qualifications: Strong background in applied machine learning and an advanced degree in a relevant field.
- Other info: Monthly team meetups in London and opportunities to mentor junior members.
The predicted salary is between 36000 - 60000 £ per year.
Direct message the job poster from DeepRec.ai
Senior Applied AI Scientist
Location: UK-based, remote-first (with monthly optional meetups in London)
Start date: ASAP
Eligibility: Must have the right to work in the UK
Overview
DeepRec.ai has the pleasure of partnering with a remote-first NbS startup as they look to hire a Senior Applied AI Scientist to lead the development of ML-driven solutions that scientifically quantify the real-world impact of nature-based interventions. You\’ll join a multidisciplinary team of AI scientists, engineers, and environmental experts tackling one of the biggest challenges of our time: building trusted, scalable tools for climate and biodiversity action.
The Culture
- Shared purpose, no ego.
- Remote-first with flexible working hours, built on trust.
- Monthly team meetups at a London-based office (Highbury).
- Clear communication, fast iteration, and support over silos.
- A culture that thrives on ambiguity, feedback, and a growth mindset.
What You’ll Do
- Design, build, and scale machine learning models using environmental and observational data.
- Apply advanced causal inference techniques such as Bayesian Neural Networks, Gaussian Processes, Difference-in-Differences, and Synthetic Control methods.
- Leverage foundation models (e.g. Prithvi, Clay) and transformers to extract insights from complex datasets.
- Work cross-functionally with science, engineering, and product teams to embed models into real-world pipelines.
- Communicate scientific and technical concepts clearly to both technical and non-technical audiences.
- Stay current with the latest developments in AI and environmental science, integrating relevant innovations into production.
- Mentor junior team members and foster best practices in applied ML.
What You Bring
- Strong background in applied machine learning, bayesian statistics, and causal inference.
- Proficiency in Python and ML frameworks such as PyTorch.
- Experience with cloud infrastructure (e.g., AWS, GCP).
- A clear, concise communication style – clear examples given when asked, not word salad.
- An adaptive mindset and comfort working in fast-changing environments.
- A deep motivation to contribute to climate and ecological impact.
- An advanced degree (MSc or PhD) in Computer Science, Statistics, Economics, Physics, Mathematics, or a related field.
Nice to Have
- Experience working with geospatial or spatial-temporal data.
- Experience with remote sensing datasets (e.g., Landsat, Sentinel, SAR).
- Familiarity with TorchGeo or TerraTorch.
- Experience with Rasterio, Geopandas, Xarray, or Dask.
- Previous collaboration with academic or scientific research communities.
- Publications in peer-reviewed journals or conferences.
Benefits
- Remote-first and flexible hours
- 32 days paid holiday (including bank holidays, fully flexible)
- Extra day off on your birthday
- Pension scheme
- Enhanced gender-neutral parental leave
- Spill mental wellbeing support
- Company laptop + home working setup allowance
Seniority level
- Not Applicable
Employment type
- Full-time
Job function
- Science
- Industries
- Research Services
#J-18808-Ljbffr
Senior Applied AI Scientist employer: DeepRec.ai
Contact Detail:
DeepRec.ai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Applied AI Scientist
✨Tip Number 1
Familiarise yourself with the latest advancements in machine learning and environmental science. This will not only help you during interviews but also demonstrate your genuine interest in the field and the company's mission.
✨Tip Number 2
Engage with online communities or forums related to AI and environmental science. Networking with professionals in these areas can provide insights into the role and may even lead to referrals.
✨Tip Number 3
Prepare to discuss your previous projects that involved machine learning and causal inference techniques. Be ready to explain your thought process, challenges faced, and how you overcame them, as this will showcase your problem-solving skills.
✨Tip Number 4
Highlight any experience you have with mentoring or collaborating in multidisciplinary teams. This aligns well with the company culture and shows that you can thrive in a remote-first environment while supporting others.
We think you need these skills to ace Senior Applied AI Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in applied machine learning, Bayesian statistics, and causal inference. Use specific examples that demonstrate your proficiency in Python and ML frameworks like PyTorch.
Craft a Compelling Cover Letter: In your cover letter, express your passion for climate and ecological impact. Mention how your skills align with the role and provide clear examples of your previous work that relate to the job description.
Showcase Communication Skills: Since the role requires clear communication of scientific concepts, include examples in your application where you've successfully communicated complex ideas to both technical and non-technical audiences.
Highlight Relevant Experience: If you have experience with geospatial data or remote sensing datasets, make sure to highlight this in your application. Mention any publications or collaborations with academic communities to strengthen your profile.
How to prepare for a job interview at DeepRec.ai
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning models, Bayesian statistics, and causal inference techniques. Bring specific examples of projects where you've applied these skills, especially in environmental contexts.
✨Communicate Clearly
Practice explaining complex technical concepts in simple terms. Since the role involves communicating with both technical and non-technical audiences, demonstrating your ability to bridge that gap will be crucial.
✨Demonstrate Your Adaptability
Highlight instances where you've thrived in fast-changing environments. The company values an adaptive mindset, so share experiences that showcase your flexibility and problem-solving skills.
✨Express Your Passion for Climate Impact
Convey your motivation to contribute to climate and ecological impact. Discuss any relevant projects or research that align with the company's mission, showing that you're not just a fit technically but also culturally.
