Location: Remote/Hybrid (India, UK, Europe, US)
Experience: 3-8+ years (flexible)
Concept X: Building the Future of Physical AI
We are an AI startup on a mission to secure the world's energy infrastructure. As the global demand for energy grows, the grid that supports it is under increasing pressure. We are building the Physical AI layer that allows energy companies to digitize, inspect, and protect their assets - from power lines to wind turbines - automatically and at scale.
Think drones, robotics, satellites from surface to space we are providing the visual intelligenceneeded for the next wave of autonomous inspections. We don't just process simple JPEGs. We blend visual, thermal, UV, LiDAR data to spot critical defects, conduct audits for new installations, analyse vegetation encroachment, and manage vast asset inventories.
Headquartered in London with a distributed engineering team across India, and commercial presence in the US, we are a global team moving fast. We are looking for builders who want to solve hard problems that impact the real world.
The Role
We are looking for a Senior Data Scientist who specializes in Deep Learning (especially Computer Vision) to join our core technical team.
We are looking for a builder someone who can both finetune existing models and develop new ones from scratch. You will be responsible for end-to-end model development: from designing architectures for multi-modal data to training, testing, and operationalising these models on our AWS cloud platform.
You will play a pivotal role in evolving our technology stack, helping us move from cloud-only inference to Edge AI deployment on drones.
What You Will Build & Own
- Next-Gen CV Models: Design and train deep learning models (Object Detection, Semantic Segmentation, Anomaly Detection) to identify asset conditions, defects, and inventory with high precision.
- Multi-Modal Fusion: Work on cutting-edge fusion algorithms that combine RGB, Thermal, and UV data to see what the human eye cannot.
- MLOps & Deployment: You won't just hand off code. You will containerise your models and oversee their deployment into production on AWS, ensuring scalability and reliability.
- Edge AI Initiatives: Lead the charge on optimising our high-performance models for edge devices, enabling real-time detection on drones and field devices.
- Continuous Improvement: Build feedback loops to monitor model performance in the wild and automate retraining pipelines.
What We Are Looking For
- Deep Learning Expertise: Strong experience with Python and deep learning frameworks (PyTorch, TensorFlow, or Keras). You understand the math behind the layers.
- Computer Vision Experience: Proven track record in building CV solutions (YOLO, Faster R-CNN, Mask R-CNN, ViTs, etc.) applied to real-world imagery. Any experience in combining visual models with LLMs (such as LVMs) is a big plus.
- Engineering Mindset: You write clean, production-ready code. You are comfortable with Git, Docker, and CI/CD pipelines.
- Cloud Native: Experience deploying ML solutions on cloud platforms (AWS preferred: SageMaker, Lambda, EC2).
- Startup DNA: You thrive in a fast-paced environment. You are self-directed, comfortable with ambiguity, and care about the business impact of your code.
Bonus Points (Desirable but not required)
- Experience with Edge AI deployment (NVIDIA Jetson, TensorRT, TFLite).
- Experience handling Geospatial Data (GIS, satellite imagery).
- Background in the energy, utilities, or infrastructure sectors.
Why Join Us
- High Impact: Your code will directly help prevent power outages, wildfires, and infrastructure failures globally.
- Cutting-Edge Tech: Work with multi-modal data (Thermal/UV) and droneschallenges you won't find in typical SaaS companies.
- Global Exposure: Collaborate with a team in UK, India, and the US, working with top-tier utility clients across continents.
- Remote/Hybrid Flexibility: We focus on output, not hours in a chair.
- Growth: As an early member of the AI team, you will have significant influence over the technical roadmap and architecture, and all the rewards that come with it
