GrowthStage
Computer Vision Engineer
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Computer Vision Engineer
Job Description: Computer Vision Engineer
About the Company
We are hiring for a Computer Vision Engineer to develop the visual understanding layer for an AI-native product.
About the Role
You will contribute to systems that interpret visual inputs, offering real-time understanding and transformation of messy data into actionable context. Key areas include:
- Screen understanding
- Object and UI detection
- OCR
- Tracking
- Segmentation
- Visual embeddings
- Video understanding
- Multimodal reasoning
This is a high-ownership technical role, ideal for someone who enjoys taking ambiguous product needs, selecting the best approach, and building production-ready systems that are fast, reliable, and impactful.
Responsibilities
- Develop real-time or near-real-time computer vision pipelines for live visual inputs
- Detect and interpret objects, UI states, entities, and scenes, as well as changes over time
- Build tracking and temporal reasoning systems to track sequential visual inputs
- Evaluate and combine OCR, object detection, segmentation, visual embeddings, Vision Language Models (VLMs), and legacy computer vision approaches
- Optimise inference across metrics: latency, throughput, model size, GPU memory, and production reliability
- Design clean APIs and event streams to integrate visual signals with product, reasoning, or automation systems
- Implement confidence thresholds, uncertainty detection, and fallback mechanisms for robust outputs
- Work closely with product and engineering teams to transition prototypes into productionised systems
- Help shape the foundation architecture for a scalable vision system
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Qualifications
Core Requirements
- Strong hands-on experience in building computer vision systems in production or production-like environments
- Proven expertise in real-time or low-latency visual processing
- Proficiency in Python and performance-oriented stacks, including:
- C++
- CUDA acceleration
- TensorRT, OpenCV, ONNX Runtime, OpenVINO, Metal, or similar
- Experience with key computer vision tasks:
- Object detection
- Segmentation
- OCR
- Visual embeddings
- Motion tracking
- Scene or video understanding
- SLAM (Simultaneous Localisation and Mapping)
- 3D/spatial computing
- Multimodal frameworks or Vision Language Models (VLMs)
- Strong intuition for trade-offs in latency, throughput, memory, confidence scoring, and reliability
- Ability to prototype quickly, measure performance, iterate, and ship
- Comfort navigating product ambiguity and selecting the most effective technical solutions
- Pragmatic engineering mindset—balancing model advances with practical reliability
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Domain Expertise
- Experience with screen capture, media streaming (WebRTC), low-latency applications for desktop or mobile
- Experience deploying CV models on constrained hardware, including:
- Edge devices
- Mobile GPUs/NPUs
- Real-time production systems
- Knowledge of usership in vision-heavy domains, such as:
- Gaming, robotics, autonomy
- AR/VR or immersive tech
- Industrial automation
- Medical imaging
- Security, surveillance
- Sports analytics
- Consumer apps (e.g., AI agents, knowledge graphs, agentic systems)
Plus Factors
- Strong open-source contributions or research demos showing visual and technical sophistication
Location and Compensation
- Preferred location: London
- Flexibility: Depends on team setup (hybrid or on-site to facilitate collaboration)
- Compensation: Competitive range for late-stage London startups:
- Base salary: £80,000-£150,000
- Equity: Included in package
- Visa sponsorship: For eligible candidates
Equal Opportunity Statement
We are committed to fostering a diverse and inclusive environment. We welcome applications from all backgrounds and identities.
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