Senior Computer Vision Data Scientist
Role details
Job location
Tech stack
Job description
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Build a thorough understanding of the end-to-end data generation pipeline, from sample preparation to downstream processing.
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Deploy and adapt our computer vision models to meet field constraints and production requirements.
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Plan data acquisition hand in hand with microbiologists by understanding deeply and taking field constraints into account
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Define and scope data acquisition needs to improve model training and generalization.
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Train, validate, and benchmark machine learning models; perform detailed error analysis to guide improvements.
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Identify bottlenecks and propose enhancements to data workflows to accelerate model development.
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Work in a multi-disciplinary environment, collaborating with R&D engineers, product managers, and clients.
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Mentor and guide junior team members, fostering technical growth and best practices., * A technical case study followed by a 45mns debrief with team members
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1 hour Founders interview
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Reference calls
You might also be invited to meet other team members at the office for a lab visit and a coffee!
This is a unique opportunity for someone who thrives on curiosity and has a genuine passion for technology. If you enjoy taking on challenges and solving complex problems, this role will provide the perfect environment for growth and impact. The ideal candidate is someone who is self-driven, eager to learn, and excited to contribute to shaping the future of microbiology monitoring. Join our innovative and dynamic team, and let's make a difference together! We look forward to meeting you!
Requirements
Do you have a Master's degree?, We value curiosity, initiative, and a growth mindset. Not every box needs to be ticked to apply.
- Education & Background: Master's degree or PhD in Data Science, Computer Science, Engineering, or a related field
- Experience (professional or academic) in Computer Vision and/or Deep Learning
- Minimum 4+ years of professional experience, with proven track record of deploying models to production
Technical Skills:
- Proficiency with PyTorch or similar deep learning frameworks
- Solid understanding of modern neural network architectures for vision tasks (e.g. Vision Transformers, segmentation networks, CycleGANs)
- Experience deploying ML models in production environments and handling operational constraints
- Familiarity with data processing and backend tools (e.g. pandas, FastAPI)
- Exposure to cloud environments (AWS, GCP, or Azure) is a plus
- Strong coding fundamentals and clean code practices, * Demonstrated ability to mentor and guide junior data scientists
- Ability to navigate and contribute in multi-disciplinary environments, including client-facing or cross-functional discussions
- Proactive, execution-oriented mindset: you take ownership and make things happen
We don't expect you to know everything from day one. What matters most is your curiosity, drive to learn, and willingness to dive into challenges.