Principal Machine Learning Engineer

at  Doublepoint

The company
Doublepoint creates gesture recognition software for smartwatches. Our technologies are being used to control AR/VR, IoT, wearables, automotive, AI assistants, TVs, and much more. Our smartwatch algorithms detect subtle hand gestures and need to be accurate, responsive, low power, and generalizable across populations. We’re a small team of 15 people based mostly in Helsinki, with 6m euro in funding from VCs and angels, and our technology is being used by over 65k people today.
The Role
We are seeking a Principal Machine Learning Engineer to spearhead our ML team. This role consists of a blend of technical leadership and hands-on coding. It requires deep and up-to-date knowledge of machine learning techniques, especially in the realm of live sensor stream-based classification. The ideal candidate will have extensive experience deploying machine learning models into real products.

Key Responsibilities

• Performance Tracking: Set standards for how performance metrics are calculated and communicated to the team and customers
• Signal Processing: Devise and implement ways of determining what information can be gathered from a signal.
• Model Development: Create and test various signal processing logic, algorithms, and neural networks to detect multiple different gestures.
• Model Improvement: Make well-informed improvements to model performance.
• Model Deployment: Deploy models securely, obfuscating our models.
• Sensor Parameter Definition: Define the sensor parameters used for optimal gesture recognition.
• Model Training: Improve model training speeds and memory efficiency.
• Team Leadership: Define model development roadmaps.

Shared Activities with Other Teams

• Data Acquisition: Devising data acquisition games and required hardware.
• Metrics Development: Devising model performance metrics with our interaction team, customers, and users.
• Hardware Specifications: Defining data acquisition, and testing hardware specifications.

Requirements

• Experience: Proven experience in developing and deploying ML models to end consumers.
• Technical Skills: Strong understanding of signal processing, time series classification, and machine learning.
• Leadership: Set a technical direction for a team, hold the team accountable to high quality and technical standards. Contribute to hiring decisions.
• Communication: Excellent communication skills, with the ability to give technical and team member feedback.

Personal Qualities

• Ambition: Desire to be part of a world-class team.
• Domain Interest: Genuine interest in human computer interaction.
• Excellence: Almost an unhealthy obsession with the quality of the things we build.
• User Centricity: Actively caring and ensuring that things we make feel great by others, not just by ourselves.
• Agency: Going beyond one’s own prescribed domain to ensure that things get done and taking responsibility for it.

Keywords
Signal Processing, Algorithm Developer, Sensors, Electrical and Electronics Engineer, Machine Learning
Doublepoint
Helsinki
Kokopäiväinen, Vakituinen
Julkaistu 22.08.202

• Performance Tracking: Set standards for how performance metrics are calculated and communicated to the team and customers
• Signal Processing: Devise and implement ways of determining what information can be gathered from a signal.
• Model Development: Create and test various signal processing logic, algorithms, and neural networks to detect multiple different gestures.
• Model Improvement: Make well-informed improvements to model performance.
• Model Deployment: Deploy models securely, obfuscating our models.
• Sensor Parameter Definition: Define the sensor parameters used for optimal gesture recognition.
• Model Training: Improve model training speeds and memory efficiency.
• Team Leadership: Define model development roadmaps