Job Title: Senior Part-Time Machine Learning Engineer (Computer Vision)
Project duration: 5 Months
Location: Remote or Hybrid (Agave Networks, London, UK)
Start Date: 1st November 2024
End Date: 31st March 2025
About Agave Networks
Agave Networks is a cleantech and deeptech startup dedicated to transforming the scrap metal and recycling industry. Our online marketplace leverages Computer Vision and Machine Learning to validate the authenticity and quality of recycled metals, enabling scrap metal yards and traders globally to openly and securely trade these reclaimed commodities, optimising transactions and promoting sustainability.
We are seeking a talented Machine Learning Engineer to contribute to our groundbreaking computer vision model aimed at grading and classifying scrap metal.
To learn more about us: https://www.agavenetworks.co/
Role Overview
We are looking for a skilled Machine Learning Engineer with expertise in computer vision to join our team on a part-time basis. In this role, you will take ownership of developing, refining, and scaling our existing computer vision model.
Key Responsibilities
- Model Development & Optimization: Enhance and fine-tune the existing scrap metal classification model, ensuring improved accuracy and reliability.
- Data Management: Manage and expand our custom dataset, implementing data augmentation techniques and balancing class distributions to improve model performance.
- Training and Testing: Conduct iterative training cycles, adjusting parameters and exploring new architectures to optimise performance.
- Evaluation & Troubleshooting: Evaluate model outputs, refine accuracy, and address issues related to object detection, annotation inconsistencies, and small object identification.
- Deployment Preparation: Prepare the model for deployment by creating pipelines for data preprocessing, model training, and evaluation using Google Cloud infrastructure.
- Collaboration: Work closely with the CTO and other team members to align model improvements with business goals and platform integration needs.
Required Skills and Qualifications
- Educational Background: Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field with a focus on Machine Learning or Computer Vision.
- Experience: At least 2 years of hands-on experience in computer vision, with specific experience in object detection and segmentation.
Technical Skills:
- Proficiency in Python and experience with machine learning frameworks (e.g., PyTorch, TensorFlow).
- Strong knowledge of computer vision libraries and tools such as OpenCV
- Familiarity with cloud-based ML environments, particularly Google Cloud and services like Cloud Run, Cloud Storage, and Colab.
- Experience with data annotation tools and processes (e.g., AWS Ground Truth, Roboflow, CVAT).
- Understanding of deployment and version control using Terraform, Docker, and CI/CD tools.
- Additional Skills:
- Strong analytical skills with the ability to interpret complex data and refine model accuracy.
- Excellent communication skills to document processes and collaborate effectively with team members.
- Experience with Infrastructure as Code (IaC) and a microservices-based architecture is a plus.
Why Join Agave Networks?
- Be part of a pioneering startup committed to sustainability and industry innovation.
- Gain hands-on experience in developing and deploying cutting-edge machine learning solutions.
- Work in a collaborative and supportive environment that values growth and development.
- Opportunity to make a tangible impact in the global recycling and waste management industry.
Work Pattern: 25 hours per week / Remote with weekly in-person meetings in London
Compensation: £2,800 per month
Application Instructions
To apply, please send your resume, a brief cover letter, and any relevant portfolio or project links to dbyrd@agavenetworks.co with the subject line “Machine Learning Engineer Application – [Your Name].” Applications will be reviewed on a rolling basis until the position is filled.
Join our team and be part of a pioneering company that is transforming the B2B recyclables-sharing industry. As a Machine Learning Operations Engineer, you will play a crucial role in developing and deploying the Object Detection endpoint, enabling our platform to provide valuable insights to our users. Apply today and contribute to our mission of revolutionising surplus sharing!