Research Scientist

About us

Note: We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.

What you will do 

• Work closely with our machine learning engineers, simulation engineers, and customers to translate physics and engineering challenges into mathematical problem formulations.


• Build models to predict the behaviour of physical systems using state-of-the-art machine learning and deep learning techniques.


• Own Research work-streams at different levels, depending on seniority.


• Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems.


• Collaborate with colleagues beyond the research team to translate your models into production-ready code.


• Communicate your work to others internally and externally as called for in paper publication venues, industry workshops, customer conversations, etc. This will involve writing for academic and non-academic audiences.


• Foster a nurturing environment for colleagues with less experience in DS / ML / Stats for them to grow and you to mentor.


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What you bring to the table

• Enthusiasm about using machine learning, especially deep learning and/or probabilistic methods, for science and engineering.


• Ability to scope and effectively deliver projects.


• Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly.


• Excellent collaboration and communication skills — with teams and customers alike.


• PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, or a related field, with particular expertise in any of the following:
  
  
  
  1. operator learning (neural operators), or other probabilistic methods for PDEs;
  
  
  2. geometric deep learning or other 3D computer vision methods for point-cloud or mesh-structured data;
  
  
  3. generative models for geometry and spatiotemporal data (VAEs, Diffusion Models, Bayesian non-parametric, scaling to large datasets, etc.).
  
  
  
  


• Ideally, >2 years of experience in a data-driven role, with exposure to:
  
  
  
  • building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications;
  
  
  • developing models for bespoke problem settings that involve high-dimensional data (spatiotemporal, geometric, physical);
  
  
  • iterating on network architectures and model structure, tuning and optimising for inductive biases, improved generalisability, and improved performance;
  
  
  • combining theoretical reasoning with empirical intuition to guide investigation;
  
  
  • formulating and running experiment pipelines to benchmark models and produce comparable results;
  
  
  • writing skills for communication complex technical concepts to peers and non-peers, tailoring the message for the required audience.
  
  
  
  


• Publication record in reputable venues that demonstrates mastery in your field, and in particular the domains of interest listed above. Desirable venues include (but not limited to): NeurIPS, ICML, ICLR, UAI, AISTATS, AAAI, Siggraph, CVPR or TPAMI/JMLR.

What we offer

• Equity options – share in our success and growth.


• 5% 401(k) match – invest in your future.


• Flexible working – balance your work and life in a way that works for you.


• Hybrid setup – enjoy our Manhattan office while keeping remote flexibility.


• Enhanced parental leave – support for life’s biggest milestones.


• Private healthcare – comprehensive coverage for you and your family.


• Personal development – access learning and training to help you grow.


• Work from anywhere – extend your remote setup to enjoy the sun or reconnect with loved ones.

What we offer

Build what actually matters

Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.

Learn alongside exceptional people

Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.

Influence over hierarchy

We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.

Sustainable pace, long-term ambition

Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our New York office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.

And it doesn’t stop there …

🚀 Equity options - share meaningfully in the company you’re helping to build.

💰 5% contribution to 401(k) - build long-term security with a strong retirement plan.

🍽️ Free team lunch 1x/week - good food, great company, and space to connect.

🏥 Private health insurance – comprehensive cover for you, offering total peace of mind.

👶 Enhanced parental leave – 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.

☀️ 20 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.

📈 Personal development – dedicated support for learning, development, and leveling up over time.

💪 Gympass / Wellhub (subsidized) – for you and up to 3 family members, supporting both physical and mental wellbeing.

💳 Flexible Spending Account (FSA) – set aside pre-tax dollars for eligible healthcare expenses.

🔎 Watch this space, we’re continuing to build this as we grow…

Salary range:

$120,000 - 240,000 depending on experience 
Seniority will be assessed throughout our interview process