Senior Embedded Machine Learning Engineer (TinyML)

Lead the design and implementation of state-of-the-art machine learning algorithms tailored for both real-world hardware and software applications;

Build and optimize embedded ML models using PyTorch and NumPy, bringing them to life in embedded systems with C and Python;

Analyze, benchmark, and fine-tune embedded ML pipelines to achieve latency, memory efficiency, and power optimization;

Pioneer explainable AI techniques that provide actionable insights into model behavior and drive trustworthy solutions for our customers and end-users;

Expand our ML toolkit by researching and integrating the latest methodologies, staying at the forefront of AI innovation;

Establish scalable, reproducible workflows that set a standard for excellence in embedded ML development;

Partner with a multidisciplinary team of hardware engineers, data scientists, and software developers to deliver integrated software and hardware application use cases;

Provide critical algorithm insights to hardware development teams to facilitate seamless integration and performance optimization;

Support the integration of ML models with hardware AI accelerators and neuromorphic processors;

Collaborate with internal teams and clients to identify and design requirements for complex customer use cases;

Translate customer needs into technical specifications and actionable project plans;

Present findings and insights to stakeholders to inform decision-making and strategy;

Mentor junior engineers and interns, fostering a culture of continuous learning and technical excellence within the team;

Contribute to the creation of intellectual property, including patents and proprietary know-how.

A BSc or MSc in a subject related to ML/Data Science/Statistics or relevant industry experience;

Solid understanding of architecture specifications, and the ability to design and develop industry-standard embedded software and methodologies;

5+ years of hands-on experience in the development and deployment of AI solutions;

Previous experience in Embedded or TinyML AI application development;

Proficiency in C/C++ for logical programming for embedded software development and Python for ML model development;

Strong experience with TensorFlow/PyTorch and Scikit-learn;

Familiarity with hardware AI accelerator architectures and neuromorphic processors;

Experience working with time series data/sensor data/real-time data processing;

Proficiency in using version control systems.

Strong analytical and problem-solving abilities with great attention to detail;

Excellent communication skills for effective collaboration with cross-functional team and stakeholders;

A proactive and self-motivated attitude toward learning and innovation.

A dynamic working environment around a fearless engineering culture;

Ambitious teams with the freedom to innovate;

A Flexible working environment (work-from-home policy, flexible working hours, advantageous holidays scheme ..);

An inclusive company culture which embraces communication, diversity and support around holistic and personal development.