AI Engineer

Currently, we’re on the lookout for an AI Engineer (EdgeAI) to join our amazing team internally.

intent has over 10+ years of experience in helping to conceptualize, design, and build apps for IoT and connected devices. We're a software house that acts as a specialized think partner for products at the intersection of physical and digital (like wearables and IoT) - from net-new to products looking to enter a competitive and established niche. Some of our clients include Oura, BOSE, and McIntosh audio systems.

💎 Requirements: 3+ years of experience in AI and machine learning, with a focus on edge computing. Min. 5 years experience in software engineering, a good command of written and spoken English (min. B2).

💰 Salary: 20-30K on B2B with uncapped commission + up to 26 paid holidays.

🏝️ Perks and benefits: remote/office (up to you), flexible working hours, additional 10 days of paid sick leave on B2B, private medical care (PZU) and Multisport card, English lessons with a native speaker, knowledge-sharing activities (company library, conference budget, team sessions).

🚀 Cool projects and clients: We are very picky in terms of clients we work with. 95% are US-based clients such as Jeep or Ōura Ring as well as super cool startups - we’ll tell you more during a call as we’re under NDAs. You will not sell sugar water for the rest of your life.

Recruitment process:

1. A screening call with an HR person (45 mins).
2. A technical interview with one of our technical recruiters (up to 1,5h).
3. Decision and feedback.

Requirements

• 3+ years of experience in AI and machine learning, with a focus on edge computing. Min. 5 years experience in software engineering
• Proven track record of developing and deploying AI models on edge devices.
• Experience with deep learning frameworks such as TensorFlow, PyTorch, and ONNX.
• Familiarity with edge computing platforms and tools (e.g., Nvidia Jetson, Google Coral, AWS Greengrass).
• Strong programming skills in Python, C++, and other relevant languages.
• Expertise in model optimization techniques for edge deployment (e.g., quantization, pruning, knowledge distillation).
• Excellent problem-solving and analytical skills.
• Ability to work in a fast-paced, collaborative environment.
• Strong communication and leadership abilities.