AddressJob Description:
As a Full Stack Machine Learning Engineer, you will play a critical role in developing and deploying innovative ML solutions, particularly in the field of computer vision. You will work across the entire Machine Learning pipeline, from dataset creation to model deployment, while leveraging your knowledge of cloud architecture, databases, and APIs. Firmware knowledge and front-end skills are also highly valued for this role.
Key Responsibilities:
- Innovate across the entire end-to-end ML production pipeline, including dataset creation, neural network architecture design, model training, fine-tuning methods, and training time optimisation.
- Implement and optimise on-device and server-side inference.
- Design, develop, and maintain software applications utilising computer vision, AI, and ML technologies.
- Implement cloud-based solutions for scalable and efficient deployment of applications.
- Collaborate with cross-functional teams to understand project requirements and deliver high-quality software solutions.
- Optimise algorithms and models for performance, accuracy, and scalability.
- Participate in code reviews, testing, and debugging to ensure software quality and reliability.
- Stay updated with the latest advancements in computer vision, AI/ML, and cloud architecture.
- Contribute to the documentation of software design and development processes.
- Quickly prototype and iterate to achieve high-quality implementations for pioneering Machine Learning algorithms.
- Collaborate with hardware and software teams to integrate research findings into market-ready solutions.
- Develop and maintain effective APIs.
Qualifications:
- Bachelor’s degree in Computer Science, Engineering, or a related field.
- 2+ years of professional experience in software development, with a focus on computer vision.
- Proficiency in programming languages such as Python and C++.
- Experience with AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, OpenCV).
- Strong understanding of cloud architecture and AWS.
- Familiarity with software development tools and practices, including version control (Git), CI/CD, and Agile methodologies.
- Excellent problem-solving skills and the ability to work independently and as part of a team.
- Strong communication skills and the ability to convey complex technical concepts to non-technical stakeholders.
- Experience in full-stack development.
- Proficiency in selecting appropriate databases and using query languages (e.g., SQL).
- Experience in both front-end and back-end development of Machine Learning systems, from data collection and model creation to deployment and maintenance.
- Experience in deploying software systems on end devices running Linux OS.
- Experience in writing and debugging firmware scripts in embedded systems.
Preferred Qualifications:
- Master’s degree in Computer Science, Engineering, or a related field.
- Experience with deep learning models in motion tracking, object detection, image segmentation, and human keypoints detection.
- [Optional] Knowledge of containerisation and orchestration tools (e.g., Docker, Kubernetes).
- Background in deploying and managing Machine Learning models in production environments.
- Knowledge of optimising cloud architecture.
- [Optional] Strong proficiency in front-end and back-end programming languages such as JavaScript, Ruby, Java, HTML, and CSS.
- [Optional] Familiarity with JavaScript frameworks such as AngularJS, React, and Ember.
About the Team:
We are an innovative team dedicated to developing cutting-edge AI and ML solutions. We believe in fostering a collaborative and dynamic work environment where every team member can thrive and contribute to meaningful projects. With us, you’ll have unique opportunities for career growth and advancement, working with a great team in a dynamic, growing, and innovative business.
How to Apply:
Please send your CV and cover letter to ****@lenexamedical.com
We’d love to hear why you would be a great fit for our team and why you’re passionate about pioneering Machine Learning solutions. Please include “Software Engineer (Full Stack Machine Learning Engineer) Application” in the email subject line
