Senior Computer Vision Data Scientist
About The Position
PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive. We are looking for a Senior Data Scientist with deep computer vision expertise to lead the development of physics-informed predictive maintenance systems for high-value industrial equipment. Working directly with major industrial customers, you will build pipelines that fuse periodic inspection imagery with equipment operating history and physics-based inputs to predict remaining component life — helping operators reduce costly unplanned interventions and optimise asset availability.
Requirements
- Strong research foundation in computer vision and applied deep learning.
- Ability to take foundation into production on real-world industrial problems.
- Ability to build models that work under difficult conditions (sparse data, inconsistent image quality, high stakes).
- Ability to move fluidly between designing the right architecture and debugging a broken data pipeline.
- Comfortable working directly with domain experts and customers.
- Deep expertise in selecting, adapting, and fine-tuning pretrained vision encoders (ViT, DINOv3, ResNet-family or equivalent) for industrial or scientific imaging problems where data is sparse and capture conditions are variable.
- Strong command of gradient-based interpretability methods (Grad-CAM, integrated gradients) and the ability to produce sensitivity maps that make model behaviour reviewable by non-ML domain experts.
- Proven ability to build joint models that combine visual features with heterogeneous inputs including tabular metadata, time-series operating history, and physics-derived signals.
- Hands-on experience with probabilistic or Bayesian output modelling and calibrated uncertainty quantification.
- Production ML mindset.
- Comfort with messy, real-world industrial datasets: sparse time series, noisy labels, irregular collection intervals, and data linkage challenges.
- Strong communication skills across technical and non-technical audiences.
- PhD or equivalent research experience in computer vision, machine learning, or a related field strongly preferred.
Nice To Haves
- Experience with physics-informed or hybrid ML approaches is a significant plus.
- Domain experience in aerospace, energy, heavy industry, mining, or MRO is helpful but not required — genuine curiosity about engineering domains and asset-intensive operations is essential.
Responsibilities
- Lead the development of physics-informed predictive maintenance systems for high-value industrial equipment.
- Build pipelines that fuse periodic inspection imagery with equipment operating history and physics-based inputs to predict remaining component life.
- Work directly with major industrial customers.
- Translate physical intuition into modeling decisions.
- Produce outputs that engineers can trust and operators can act on.
- Architect and ship reliable, scalable pipelines deployable within enterprise cloud environments.
- Co-develop solutions on-site with customers.
Benefits
- Equity options
- 5% contribution to 401(k)
- Free team lunch 1x/week
- Private health insurance
- Enhanced parental leave (3 months full pay paternity and 6 months full pay maternity leave)
- 20 days of Annual Leave (+ Public Holidays)
- Personal development support
- Gympass / Wellhub (subsidized)
- Flexible Spending Account (FSA)
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What This Job Offers
Job Type
Full-time
Career Level
Senior
