Models – Machine Learning Engineer
At Audio Analytic, we have built a market for artificial audio intelligence within the high-volume consumer electronics sector, and we’ve signed a number of high-profile marquee customers. We are recognised as the leaders in the field of AI and sound recognition both by our customers and by market commentators such as IDC and Wired.
As a Machine Learning Engineer, you will be responsible for producing the machine learning models – trained on our vast audio datasets – that form the core of exciting new products for our customers and their millions of users, and at the same time helping Audio Analytic towards its aim of giving all machines a compact sense of hearing.
Your primary responsibilities will include:
- Using machine learning techniques to train, debug, and evaluate models for customer deliveries ranging from quick prototypes to full production-level models.
- Performing exploratory data analysis on the large audio datasets we have in Alexandria, our data platform, to develop greater understanding of the problem domain.
- Working with our platforms engineers and MLOps engineers to contribute to, and guide, tool development and provide feedback for newly implemented features.
- Working with the Data team to guide audio data collection campaigns and labelling policies to ensure we get the best training and evaluation data possible.
- Providing feedback to product owners on project requirements and supporting feasibility and planning exercises.
This role is mostly focussed on the model creation aspects of ML engineering. We are also looking for ML Engineers focussed on software engineering – see the Software – Machine Learning Engineer role.
Skills and personal attributes
- Experience using Python and common data- and machine learning-related libraries, e.g. numpy, scipy, pandas, matplotlib, or similar languages (e.g. R, Julia).
- Practical knowledge of applying machine learning or statistical techniques to solve real-world problems (not necessarily in the audio domain).
- Excellent written and verbal communication skills, including the ability to clearly convey insights from numerical data to diverse audiences.
- Proficiency using the command line including shell scripting, ideally in a Unix-based environment (e.g. Linux, macOS).
- A drive to learn and master new technologies and techniques.
- Experience with Keras/TensorFlow or Pytorch.
- Knowledge of basic audio or signal processing techniques.
- Experience using AWS, GCP, Azure or other cloud computing platforms.
- Embedded computing experience, e.g. tinyML.
- Experience with data visualisation tools, e.g. Redash.
- Experience with experiment tracking tools, e.g. MLFlow.
- MLOps experience.
Education and experience
- A first-class or 2:1 degree in a STEM subject.
- At least one year of work experience.
As part of your education or work, you must have spent at least one year with a significant focus on machine learning or data science.
Offices are in Cambridge City centre. Casual dress code, informal and sociable atmosphere, and a good work / life balance. Most of us are currently working remotely due to COVID-19. As more people return to the office, where jobs allow, we will support flexible working in terms of days spent in or away from the office.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
We offer a highly competitive range of benefits to help you live well, plan ahead and have fun. These include free gym membership, private healthcare, life assurance and free pizza. See more at https://www.audioanalytic.com/careers/benefits/