Edge AI Engineer

About the role

As an ML Engineer at Sigma, you will contribute to the development of advanced edge AI solutions. This role involves designing, optimizing, and deploying machine learning models directly on embedded devices, working within a dynamic cross-functional team. You will drive innovation in areas like computer vision and sensor fusion, ensuring cutting-edge AI capabilities are integrated into real products.

This is an opportunity to work with AI that is actually deployed in end products, where your work has direct impact on users. You will join an environment focused on innovation, collaboration, and continuous development.

You are offered

• The opportunity to work on cutting-edge AI projects that shape the future of technology
• Challenging and diverse projects that push your skills and expertise to the next level
• A chance to grow your career within a global company, supported by an innovative and collaborative team
• A strong focus on work-life balance, with flexible hours and options for remote work

Work tasks

This role focuses on developing and optimizing ML models for tasks such as gesture recognition, defect detection, object tracking, and contextual human-machine interaction, deployed on edge hardware including Qualcomm, NVIDIA, NXP, and other MCU-class systems.

• Design, train, and validate ML models for computer vision, sensor fusion, and predictive analytics.
• Develop and optimize ML pipelines for on-device inference, including quantization and DSP/NPU acceleration.
• Build data ingestion, preprocessing, and feature-engineering pipelines for edge and hybrid deployments.
• Work with cross-functional teams to integrate ML functionality into real products.
• Participate in prototyping, Proof-of-Concepts, customer dialogues, and technical presentations.
• Stay updated with the latest trends, tools, and technologies in AI/ML.

We are looking for

• Academic background in Machine Learning, Robotics, Autonomous Systems, or related fields
• Strong Python skills and experience with ML frameworks (PyTorch or TensorFlow)
• Knowledge of quantization, model compression, benchmarking, and inference profiling on constrained hardware
• Proven ability to develop and deploy ML models in production or real-world projects
• Experience with at least one CV or classical ML library (OpenCV, scikit-learn, etc.)
• Experience designing or contributing to data pipelines (validation, augmentation, or performance analysis)
• Fluent in English

It is meritorious if you have

• Experience building and deploying ML models for Edge/Embedded platforms (SoCs like Qualcomm, Nordic, or NXP)
• Experience in computer vision, time-series/sensor-data ML, or LLM-based/hybrid AI systems
• Knowledge of MLOps, FastAPI, Docker, CI/CD, and cloud platforms such as Azure or AWS
• Understanding of the end-to-end ML lifecycle from experimentation to production deployment

To succeed in the role, your personal skills are:

• Supportive
• Goal oriented
• Responsible
• Intellectually curious

Our recruitment process

This recruitment process is handled by Academic Work and it is our client’s wish that all questions regarding the position is directed to Academic Work.

Our selection process is continuous and the advert may close before the recruitment process is completed if we have moved forward to the next phase. The process includes two tests: one personality test and one cognitive test. The tests are tools to find the right talent for the right position, to enable equality, diversity, and a fair process.

Sigma Connectivity AB

Sigma Connectivity is a global leader in innovative technology solutions with over 19 years of experience. We specialize in developing customized hardware and software solutions, particularly connected products in consumer electronics and IoT. Our team consists of 700 engineers from 25 nationalities, working to deliver scalable, reliable, cost-effective, and secure solutions. We foster a culture of knowledge sharing combined with a Nordic work ethic.