2
Home Experience
Machine Learning Engineer
As a member of the HomeX R&D team, you will be responsible for the implementation and operation of AI solutions targeting the Home Services domain. Your focus will be on the development of Computer Vision solutions, while working closely with our Natural Language Processing and Knowledge Graph team, to create a system that deeply understands home repair and maintenance in HVAC, electrical and plumbing systems, and domestic appliances. You will also work with HomeX’s Product Engineering team to ensure that your work contributes to our core product and service offerings in Intelligent Diagnostic Solutions.
As a member of the HomeX R&D team, you will be responsible for the implementation and operation of AI solutions targeting the Home Services domain. Your focus will be on the development of Computer Vision solutions, while working closely with our Natural Language Processing and Knowledge Graph team, to create a system that deeply understands home repair and maintenance in HVAC, electrical and plumbing systems, and domestic appliances. You will also work with HomeX’s Product Engineering team to ensure that your work contributes to our core product and service offerings in Intelligent Diagnostic Solutions.
About You
You are a Machine Learning Engineer with the ability to create simple solutions to complex problems. You are comfortable applying state-of-the-art machine learning techniques to new problem spaces, resulting in practical solutions that solve real problems for real customers. You are able to deliver solutions as a series of incremental improvements that continually add value.
You understand the principles of well-architected software and systems including operational excellence, scalability and resilience. You know that all these principles are important and are able to articulate their importance to your peers. You have a continuous improvement mindset, which you apply in to ensure the highest level of service possible.
You are a hands-on contributor who embodies the value of teamwork, discussion and consensus-building. You are able to drive initiatives forward both as an individual and as part of a team. You encourage and facilitate professional and personal growth in your peers.
You are driven by delivering maximum value at all times. You enjoy working in a scrappy, startup environment where the only constant is change, and adapting to change is something you thrive on. You can collaborate with colleagues from a variety of backgrounds such as designers, engineers, product managers.
We know that no two career paths look the same, so the list of qualifications and experience below should be viewed as a ‘wish-list’, rather than hard-and-fast requirements. We have a culture of continuous development at HomeX, so we would love to hear from you, even if you don’t tick all of our boxes just yet.
Key Qualifications
- Master’s degree (or PhD) in Computer Science, Machine Learning, Data Science or a closely related field.
- Experience with the entire machine learning lifecycle (design, training, deployment, evaluation and updating).
- Proficiency in deep-learning architectures and techniques including convolutional neural networks, transformers, transfer learning, semi-supervised learning and data augmentation.
- Familiarity with ML-based approaches to computer vision tasks including image classification, object detection, instance segmentation, scene reconstruction and scene understanding.
- Practical experience using Python and popular ML frameworks (Pytorch, Tensorflow) to implement novel solutions based on established and emerging techniques.
- Solid knowledge of data structures, object-oriented programming and software engineering principles.
- Excellent written and verbal communication skills.
Preferred Qualifications
- Industry experience developing ML-based computer vision solutions for image and video.
- Good knowledge of state-of-the-art research in ML-based computer vision.
- Experience constructing and deploying entire ML pipelines in the cloud.
- Working knowledge of deployment in cloud-based environments (such as Google Cloud Platform).
- Familiarity with developing and operating ML models on edge devices.