Senior/Lead Machine Learning Engineer

Established in 1997, Softeq was built from the ground up to specialize in new product development and R&D, tackling the most difficult problems in the tech sphere. Now we've expanded to offer early-stage innovation and ideation plus digital transformation business consulting. Our superpower is to deliver all of this under one roof on a global scale. So let's get started and build a better future together!

Location: Europe, 100% remote work (B2B contract directly with Softeq)

We are looking for an experienced Software Engineer with the expertise in Machine Learning to spearhead the development of cutting-edge ML/DL models tailored for ultra low-power devices. You will play a key role in the end-to-end pipeline—from sensor data acquisition and signal processing to model optimization and deployment on microcontrollers. 

Key Responsibilities

• ML/DL Model Development 

• Design, implement, and optimize ML/DL models for ultra low-power devices, focusing on efficient use of limited resources. 

• Collaborate with firmware developers to integrate models into embedded systems. Signal Processing & Feature Extraction 

• Process and analyze sensor data (e.g., accelerometers, GPS) to extract meaningful features and insights. 

• Leverage advanced signal processing techniques and algorithms to improve data quality and model accuracy. Data Collection & Management 

• Curate and manage datasets, ensuring data quality and relevance for training and testing. 

• Oversee data collection processes, coordinate sensor setups, and validate incoming data for consistency and accuracy. Model Optimization 

• Implement and maintain model compression, quantization, and pruning techniques for microcontrollers. 

• Conduct performance analysis and benchmark models across different hardware platforms. 

Collaboration & Leadership 

• Work closely with firmware developers to ensure smooth model integration and real-time deployment. 

• Mentor junior engineers, provide technical guidance, and help shape the overall ML roadmap. 

Qualifications Education & Experience 

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field; PhD is a plus. 

• Software engineering experience with experience in designing and deploying ML/DL models, with a strong emphasis on signal processing. 

• Good level of English (both written and spoken), min. B2+

Technical Skills 

• Proficiency in Python and at least one deep learning framework (e.g., TensorFlow, PyTorch). 

• Strong understanding of signal processing algorithms (Fourier transforms, filtering, denoising, feature extraction). 

• Experience with sensor data (accelerometers, GPS) and data collection pipelines. 

• Hands-on experience with embedded systems and microcontroller-based deployments. 

• Familiarity with model optimization techniques such as quantization, pruning, and knowledge distillation. 

• Comfortable with Git, CI/CD pipelines, and version control best practices. Soft Skills 

• Excellent problem-solving skills and attention to detail. 

• Strong communication and collaboration abilities. 

• Ability to work effectively in a fast-paced, cross-functional environment. 

Nice to Have 

• Familiarity with C/C++ for embedded firmware development. 

• Experience with ultra low-power device constraints and power management techniques. 

• Prior contributions to open-source ML or signal processing projects. 

• Knowledge of hardware design and sensor fusion techniques.