Edge AI Engineer

Sigma Industry Innovation AB; Lunds kommun; On-site; SEK 480,000 - 600,000; Full time

Benefits offered by this job

Flexible hours

Remote work options

Health and wellness benefits

25 days of annual paid vacation

Job summary

Sigma Industry Innovation AB in Lund is seeking a talented professional to work on cutting-edge ML projects involving computer vision, AI, and sensor fusion. The role emphasizes designing, training, and deploying ML models, ensuring accuracy and performance on various hardware platforms.

Ideal candidates possess strong skills in Python and machine learning frameworks, with at least 2 years of hands-on production experience. The company offers a vibrant work environment, competitive pay, and generous benefits including 25 annual vacation days.

Qualifications

• Strong hands-on experience in developing and deploying ML models for Edge or Embedded platforms.
• 2+ years of hands-on experience developing and deploying ML models in production.
• Understanding of end-to-end ML lifecycle, including experimentation, evaluation, and deployment.

Responsibilities

• Design, train, and validate ML models for computer vision and predictive analytics.
• Build data processing and analysis pipelines for edge and hybrid deployments.
• Collaborate with cross-functional teams to integrate ML functionality into products.

Skills

Python

Machine Learning frameworks (PyTorch, TensorFlow)

Computer Vision (OpenCV, scikit-learn)

Data pipelines

Effective communication skills

Education

Master's or PhD in ML, Robotics, Autonomous Systems or related fields

Tools

Docker

FastAPI

Azure or AWS

Job description

Sigma Connectivity's Edge AI initiatives span multiple domains—computer vision, audio intelligence, sensor fusion, and embedded ML—delivering low‑latency, privacy‑preserving intelligence directly on devices across diverse hardware platforms. Projects routinely involve 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. Work includes quantization, DSP/NPU acceleration, real‑time analytics, and combined cloud‑edge pipelines that enhance precision while keeping compute close to the data source.

Your work will include

Model Design and Deployment: On-Device

• Design, train, and validate ML models for computer vision, sensor fusion, signal processing, and predictive analytics.
• Develop and optimize ML pipelines for on‑device inference, including quantization, power/performance tuning, and DSP/NPU acceleration.
• Monitor, test, and optimize the performance of deployed models to ensure accuracy, scalability, and maintainability.

Data Processing & Analysis

• Build data ingestion, preprocessing, and feature‑engineering pipelines for both edge and hybrid (Edge + Cloud) deployments.
• Extract, process, and analyse large datasets to generate actionable insights and continuously improve model performance.

Collaboration

• Work with cross‑functional teams—architects, embedded developers, PMs, UI/UX, and customers—to develop and integrate ML functionality into real products.
• Participate in prototyping, PoCs, and contribute to customer dialogues and technical presentations.
• Document work and clearly explain trade‑offs and decisions behind solutions.

Stay Current

• Keep up to date with the latest trends, tools, and technologies in AI/ML to ensure our solutions are cutting‑edge.

We are looking for

• Strong hands‑on experience in Python, ML frameworks such as PyTorch or TensorFlow, and classical CV libraries (OpenCV, scikit‑learn).
• Ability to build and deploy ML models for Edge or Embedded platforms, preferably with experience on Qualcomm, Nordic, NXP, or similar SoCs.
• Familiarity with quantization, model compression, benchmarking, and inference profiling on constrained hardware.
• Experience with data pipelines, including data validation, augmentation, and performance analysis.
• Understanding of end‑to‑end ML lifecycle, including experimentation, evaluation, and deployment in production environments.
• Master's or PhD in ML, Robotics, Autonomous Systems or related fields.
• 2+ years of hands‑on experience developing and deploying ML models in production.
• Proven experience in one or more of:
  • Computer vision
  • Time‑series or sensor‑data ML
  • LLM‑based or hybrid AI systems
• Effective communication skills and experience working in cross‑functional teams.
• Passionate about staying up to date with emerging technologies, methodologies, and industry trends in AI/ML.
• Bonus: Knowledge of MLOps, FastAPI, Docker, CI/CD, and cloud platforms such as Azure or AWS.

We Provide

• Cutting‑Edge Projects: Opportunity to work with industry‑defining technologies in applied research and functional innovation.
• Vibrant Work Environment: Technical experts from 25 nationalities, daily disruptive ideas, and creative solutions to enhance edge performance.
• Work‑Life Balance: Flexible hours and remote work options to maintain balance.
• Competitive Pay: Salary aligned with industry standards.
• Generous Vacation Time: 25 days of annual paid vacation.
• Health and Wellness Benefits: Dedicated yearly health and wellness allocation.