Deep Optica
Chief AI Scientist (AI4Mining Startup Executive)

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About Deep Optica
Deep Optica is an AI4Science company building a Mining World Model — a system that integrates geological, geophysical, geochemical, remote sensing, and drilling data into probabilistic subsurface representations. Our data foundation includes 200,000+ engineered drillholes and 1,500 block models. We deliver this through expert-led exploration services and agent-based software, helping miners and investors evaluate assets in early-stage exploration and transactions. Deep Optica exists to prove what an AI-native mining company can be.
The Role
Full-time, hybrid, based in London and/or Shanghai. You will join as a founding executive — the scientific architecture of the Mining World Model and the company's AI research direction will carry your imprint. You will own the AI research agenda, working closely with our co-founders and scientist team — PhDs and scholars in mathematics, AI, data science, and geology — to fuse frontier AI with deep domain science.
- Track the frontier of AI research across the full landscape — foundation models, agentic systems, probabilistic and physics-informed methods, spatial and multi-modal learning — and judge which advances genuinely apply to the Mining World Model
- Define the AI architecture of the World Model: how multi-modal geoscience data becomes probabilistic subsurface representations, and how uncertainty is quantified, propagated, and communicated
- Lead the AI research team and partner with our CTO to drive R&D and product development from research idea to shipped capability
- Set scientific standards for the AI function: reproducibility, validation against ground truth, and honest characterization of model limits
- Represent Deep Optica's technical vision with clients, investors, and partners; help shape product roadmaps and company strategy
- Build and mentor a world-class AI research function as the company scales
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What We're Looking For
- PhD or equivalent research depth in machine learning, applied mathematics, statistics, physics, or a related quantitative field
- Demonstrated command of the current AI frontier and its direction of travel — study, evaluate, and reproduce new research as a matter of habit, and can separate durable advances from hype
- Track record of taking ML research from idea to deployed system, ideally on scientific, geospatial, or physical-world data
- Strong command of probabilistic methods and uncertainty quantification — this is central to the role, not a nice-to-have
- Experience with one or more of: 3D/spatial deep learning, graph neural networks, physics-informed ML, foundation models, Bayesian inference at scale
- Fluency in modern ML engineering
- Demonstrated ability to lead research teams and set technical direction
- Genuine curiosity about the physical world — you want your models grounded in geology, and you're eager to learn from domain experts
- Ability to explain model behaviour, assumptions, and uncertainty to boards, investors, and non-technical stakeholders
- Comfortable working with a global, cross-cultural team
- Mining or geoscience exposure is a plus but not a must


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What We Offer
Founding executive standing: you define the AI standard the company is judged by, with senior executive scope and meaningful equity participation — backed by top venture investors and teams across Asia, Europe, and North America.
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