About Entrupy
Entrupy is a global technology company whose mission is to protect businesses, borders and consumers from transacting in counterfeit goods. Entrupy has developed a patented technology system which utilizes a combination of AI and computer vision to instantly identify and authenticate high value physical goods.
Entrupy's solutions serve business customers including leading luxury brands, retailers, e-commerce marketplaces and online resellers in over 60 countries. Entrupy is growing quickly with team members based in the US, India, Japan and Brazil. Entrupy's solutions in market:
- Entrupy Apparel Authentication
- Entrupy Bags & Leather Goods Authentication
- Entrupy Sneaker Authentication
As we continue to build...
We're seeking curious, growth minded thinkers to help shape our vision, structures and systems; playing a key-role as we launch into our ambitious future. If you're invigorated by our mission, values, and drive to change the world — we'd love to have you apply.
About the role
We are seeking a Machine Learning Engineer with expertise in classical Computer Vision and Deep Learning to contribute to the development of advanced computer vision algorithms focused on item authentication and fingerprinting.
In this role, you will drive the research, development, and deployment of state-of-the-art algorithms and models aimed at accurately determining the authenticity of items and assigning unique digital identities through image analysis. You will also oversee the optimisation of image capture solutions on edge devices and ensure models are interpretable, scalable, and robust.
As a senior team member, you will collaborate cross-functionally to define and deliver impactful projects and contribute to thought leadership in the computer vision domain.
Reports to: ML Manager
Location: Remote: Austria, Bulgaria, Hungary, Romania & India
What You'll Do:
- Define the technical roadmap for computer vision projects, aligning with business goals and customer needs.
- Mentor and provide technical guidance to junior engineers, fostering a culture of collaboration, innovation, and excellence.
- Design and develop cutting-edge computer vision models and algorithms for item authentication, fingerprinting, high-quality image capture and related applications.
- Lead innovation by staying ahead of trends in computer vision and machine learning, introducing novel techniques to improve model performance and scalability.
- Oversee the deployment of machine learning models in production, ensuring robustness, efficiency, and seamless integration into systems.
- Optimise algorithms for edge device deployment, focusing on latency, accuracy, and power consumption.
- Work closely with internal and external stakeholders to understand product requirements, define project scopes, and deliver actionable solutions.
- Collaborate with engineering teams to integrate CV models into broader system architectures while maintaining system reliability and performance.
- Drive best practices in code quality, testing, and documentation. Review and refine code, ensuring modularity, reliability, and adherence to industry standards.
- Analyse production data to identify opportunities for continuous improvement in algorithms and systems.
Who you are:
- Education: Bachelor's or Master's in Electronics, Physics, Computer Science, or related field.
- Experience: 3-6 years in computer vision and machine learning development.
- Core Expertise:
- Proficient in both traditional CV techniques (feature extraction, image processing) and deep learning methodologies.
- Advanced knowledge of Python and C++, with expertise in frameworks such as PyTorch, HuggingFace, OpenCV, and CUDA.
- Extensive experience in designing, training, and deploying CV models at scale, including distributed training and inference pipelines.
- Expertise in API design and deployment for ML model services such as FastAPI, TensorRT, Nvidia Triton, and Ray.
- Mathematical Proficiency: Strong foundation in probability, statistics, optimisation, linear algebra, and geometry.
- EdgeML Experience: Skilled in deploying and optimising models for iOS devices, with a focus on real-time data processing and resource efficiency.
- Collaboration & Communication: Ability to articulate technical concepts and collaborate in cross-functional, global teams.
- Ownership & Drive: A proactive approach, a high degree of ownership, and an eagerness to tackle complex challenges.
What we offer
- Market-competitive and pay equity-focused compensation structure
- Generous time away, including company holidays, paid time off, sick time, parental leave, and more!
- The agency to innovate, directly impacting product features and customer experiences.
- Opportunity to be part of the core team in a growing setup.
- Opportunities to publish research, contribute to patents, and further develop CVML and edgeML expertise.
Working Hours & Collaboration
We are a globally distributed team across the globe, and this role requires regular collaboration across time zones. To maximize overlap with teammates, we typically begin our day around 10:00 AM IST (approximately 6:30 AM Austria time).
While we maintain core collaboration hours, we also value flexibility and ownership. We focus on outcomes rather than clock-watching and encourage team members to manage their schedules in a way that balances effective teamwork with personal flexibility.
We have had an incredible run so far and are laying the foundation for a culture that is fast-paced, entrepreneurial, and rooted in passion, kindness, and positivity. We live by these values – we hire by them, promote them, and celebrate them every day.
If you are a visionary Computer Vision / ML engineer with extensive experience in crafting production-ready solutions, a passion for mentoring, and a desire to solve impactful challenges, we'd love to connect!
Entrupy embraces a diversity of backgrounds and experiences and provides equal opportunity for all applicants and employees. We are dedicated to building a company that represents a variety of backgrounds, perspectives, and skills. We believe that the more inclusive we are, the better our work (and work environment) will be for everyone.
