Overview
We’re looking for a Computer Vision Engineer focused on bringing advanced vision models into production. You’ll own the full lifecycle of CV systems — from model integration and orchestration to deployment on cloud and edge environments. Your role Develop and deploy computer vision models for real-world video and sensor applications Build reliable training, evaluation and inference pipelines for large-scale data Operate and optimise GPU clusters, Docker/Kubernetes environments and cloud workloads Implement CI/CD, versioning and orchestration for ML pipelines Collaborate with research engineers to transition prototypes into scalable, production-grade systems Work with robotics and platform teams to ensure robust deployment at the edge You are 5–7 years experience in computer vision, ML engineering or production AI systems Strong in Python, PyTorch and modern CV architectures (e.g. tempora
Full job description
Description
Full Job Description
We’re looking for a Computer Vision Engineer focused on bringing advanced vision models into production. You’ll own the full lifecycle of CV systems — from model integration and orchestration to deployment on cloud and edge environments.
Your role
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Develop and deploy computer vision models for real-world video and sensor applications
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Build reliable training, evaluation and inference pipelines for large-scale data
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Operate and optimise GPU clusters, Docker/Kubernetes environments and cloud workloads
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Implement CI/CD, versioning and orchestration for ML pipelines
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Collaborate with research engineers to transition prototypes into scalable, production-grade systems
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Work with robotics and platform teams to ensure robust deployment at the edge
You are
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5–7 years experience in computer vision, ML engineering or production AI systems
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Strong in Python, PyTorch and modern CV architectures (e.g. temporal transformers, detection, tracking)
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Experienced with containerisation and orchestration (Docker, Kubernetes, MLFlow, Airflow, etc.)
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Familiar with distributed training, GPU management and inference optimisation
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Solid understanding of cloud infrastructure (AWS or similar) and MLOps tooling
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Pragmatic engineer — focused on reliability, reproducibility and maintainability
Nice to have
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Experience deploying CV models on edge devices or embedded systems
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Familiarity with TensorRT, quantisation, and real-time inference optimisation
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Background in video analytics, action recognition or multi-modal perception
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Understanding of model orchestration frameworks and large data pipelines
Why this role matters
You bridge research and production — turning cutting-edge computer vision models into robust, real-time systems that power intelligent industrial automation.
What we offer
Employee Share Options Program for all permanent employees*
An increasing benefits list: currently includes Urban Sports club and quarterly team retreats.
Be on the forefront in defining what artificial intelligence means in manufacturing
Gain hands-on experience in working in an AI-first software company
Supportive and inclusive culture that values diversity and promotes the advancement of underrepresented groups within the company
Collaborate with a diverse (currently more than 10 nationalities) and talented team, working on cutting-edge projects with real-world impact
Network with professionals and leaders in the field, opening doors to potential future career opportunities
We have a very flat hierarchy, open 360° feedback, and flexible working hours
Ethics⚖: We are committed to developing ethical AI software
Don't meet all the requirements?
Almetra is committed to creating a workplace that is diverse, fair, and inclusive. We encourage candidates from all backgrounds, even if they do not meet every qualification, to submit their application. We firmly believe that having a team with diverse perspectives only strengthens our company and drives innovation. Our commitment also extends to providing an accessible environment for everyone, including those with disabilities. Please let us know if you require any accommodations during the application process or while working with us, and we will do our best to support you.
*Only full-time, permanent roles are eligible for stock options. Part-time roles, contract roles, work-student, internships and freelance roles are not eligible for stock options.
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