Senior Deep Learning Research Engineer

At Greyparrot, we build the eyes of a circular economy and are dedicated to creating tangible value for the waste recycling industry, reinventing current systems to better our society.

The Team & Environment

You will report directly to the Head of Deep Learning. You will work within a focused DL team and collaborate with a dedicated Data team. You will also regularly interact with the wider company to ensure technical alignment across the organisation. If you live in London or within commuting distance, we’d like you to come into the office at least once a week. If you’re elsewhere in the UK, we ask you to come in once a month, and for our Quarterly All Hands.

What to expect from the role

As a Senior Deep Learning Research Engineer, you are an architect of a sustainable future. You will have the autonomy to propose, discuss, and implement the best solutions for our customers. If you are motivated by the challenge of applying cutting‑edge Deep Learning in messy, real‑world environments where your input directly reduces the global carbon footprint, you are in the right place.

Key responsibilities

• Pushing the boundaries of deep learning by building upon the latest research in object detection and classification.
• Developing deep learning methods using best software development practices; training, analyzing, and reporting model performance.
• Developing internal tools to further automate research and analysis workflows.

Qualifications

• 3+ years (5+ preferred) applying deep learning in industry settings.
• Experience with applying latest Deep Learning research in PyTorch.
• Experience with active learning, semi-supervised learning, learning from noisy labels, model robustness (at least two).
• Experience with architectures such as YOLO, ViT, ResNet.
• Ability to write clear, efficient, and scalable code using Python and PyTorch.
• Experience with numpy, scipy, OpenCV, Albumentations.
• Analytical detail‑oriented mindset with strong abstract thinking and a solid theoretical understanding of neural networks.

Nice-to-have extras

• Experience in the waste industry.
• Startup or scale up experience.

On offer

• Competitive London‑based salary (salary band available upon application) + Employee stock option scheme.
• Customised hybrid working between office and home.
• 25 Days Holiday plus Bank Holidays in UK (or statutory country‑equivalent if higher): Additionally, carry over up to 3 unused holiday days each new year.
• Paid sick leave for physical and mental health needs.
• Unlimited Healthy Snacks: Fuel your day with a variety of fresh fruit, tea, coffee, and healthy snacks every time you’re in the office.
• Enhanced Parental Leave: Experience comprehensive support with enhanced maternity, paternity, adoption, or shared parental leave.
• Learning and Development Budget: Invest in your professional growth with a dedicated budget of £500 per year.
• 1‑1 Mental Health Support: Prioritize your mental well‑being with personalized support and 1‑1 therapy provided by Spill.
• Summer Friday Half‑Days: Celebrate the warmer months with Friday half‑days.
• Cycling Benefits: Take advantage of our cycle to work scheme, allowing you to purchase a bicycle through salary sacrifice, saving at least 26%, or opt to rent a bicycle for up to 12 months.
• Home Office Budget: Enhance your remote work setup with a yearly budget of £500 dedicated to equipping your home office with the tools and resources you need for optimal productivity.
• Nomad Working: Immerse yourself in the freedom of nomadic work with our 12‑day allowance, usable within a 1‑3 hour time difference.

A few things to note

Not open to recruiters. Only applicants who have the right to work in the UK will be considered at this time. Please note that we will filter screening questions for authenticity; pure AI‑generated answers will result in automatic disqualification. We want to hear your voice and personal experience. We are 100% committed to building a diverse and representative team. Whatever your race, religion, colour, national origin, gender, sexual orientation, age, marital status, or disability - we want to hear from you.