 at Spoor you'll be joining a world-class engineering team to lead our research efforts in developing a system for detecting, tracking and classifying objects in motion (specifically birds) at or near wind farms.

Lead research projects, mentor research engineers, and stay abreast of the latest methods and models in computer vision and AI

Contribute to the technical culture of the company by defining and maintaining research standards, methods, and best practices

Research, evaluate and implement state-of-the-art deep learning computer vision models for application at Spoor

Take the application of AI in the biodiversity field to the next level!

Masters or Phd degree in Computer Science, Applied Mathematics or related field

Experience with productionising research projects

Experience using tools such as:  Python, C/C++, OpenCV, Tensorflow, Keras, PyTorch or similar

You have strong analytical/mathematical and problem solving skills

You’re a team player and get things done

A high quality of life and security in beautiful Norway

A flexible working environment with freedom to tailor your work situation and hours to suit your life situation

An opportunity to grow and learn as a professional and as a person

A diverse and inclusive workplace and an opportunity to make a difference

Work in a world-class team with exceptional talent on important problems

 and Helge Reikerås who found each other in the Antler startup accelerator program in Oslo, Norway. The founders connected on a shared passion for renewable energy, sustainability and artificial intelligence. Spoor has received financial support from several of the Nordic’s most active investors: Antler, Startuplab, Firda, Wiski Capital, Nysnø, Ørsted, and Norrsken.

Lead Research Engineer

 at Spoor you'll be joining a world-class engineering team to design and build the cloud infrastructure at Spoor.

Have the key responsibility for designing and building Spoor’s cloud platform

Collaborate with engineering and development teams to evaluate and identify optimal cloud solutions.

Educate a broader team on the implementation of new cloud technologies and initiatives.

Develop and maintain cloud solutions in accordance with best practices.

Ensure efficient functioning of data storage and processing functions in accordance with company security policies and best practices in cloud security.

Identify, analyze, and resolve infrastructure vulnerabilities and production deployment issues.

Regularly review existing systems and make recommendations for improvements.

Degree in computer science or a similar field.

At least 2 years of experience in the field of cloud computing.

Experience with a major cloud provider (AWS, Google Cloud, Microsoft Azure)

Good communication and collaboration skills.

Experience with AWS preferably AWS certification

Previous experience working on production AI/ML systems

Cloud Engineer

 Spoor is one of Norway’s most promising deep-tech startups. Our mission is to enable nature and industry to coexist, and our initial focus is on monitoring and protecting birdlife within offshore and onshore windfarms worldwide. We apply Artificial Intelligence to gather and analyze bird activity data and enable the environmentally-responsible rollout of clean energy worldwide.

 As a Product Manager in Spoor you'll be joining an ambitious, collaborative, diverse, and purpose-driven team, to help define the future of wildlife monitoring, biodiversity reporting, and best practices for reducing adverse biodiversity impacts.

Gather and prioritize product objectives and customer requirements from multiple stakeholders

Build strategic product roadmap and make strategic decisions on feature/value development together with management

Create product strategy documents that describe business cases, high-level use cases, technical requirements, support revenue, and ROI targets with product strategy

Work closely with the tech and commercial team to deliver on best-in-class product

Communicate a product vision both internally and externally

Drive the product throughout the product life cycle


Bachelor's degree or higher, and/or several years of product-focused work experience

Thrive working in high-paced, innovative environments

Professional standard spoken and written English, additional languages are an advantage

Ability to understand and prioritize input from different stakeholders

Ability to build a great product roadmap and communicate it to different stakeholders

Product Manager

 at Spoor you'll be joining a world-class engineering team to design, develop and deploy a system for detecting, tracking and classifying objects in motion (most importantly birds) at or near wind farms.

Configure and optimise Spoor’s AI computer vision models to run on edge devices

Build systems to monitor performance and availability of edge devices in the field

Discover, benchmark and propose new available edge AI technology for improved performance, reliability and cost

Bachelor's degree or higher in Computer Science or related technical field

Experience with edge AI technologies such as: Nvidia Jetson, Google coral or similar

You have strong analytical, mathematical and problem solving skills

Computer Vision Engineer (edge)

 at Spoor you'll be joining a world-class engineering team to design and implement processes and systems that are performance and scalable in deploying machine learning models to cloud and edge efficiently and reliably.

Develop processes and systems to deploy machine learning models at scale

Discover, benchmark and propose new AI architecture solutions and services for better developer experience and efficiency

Develop and deploy scalable tools for engineering team to handle machine learning training and inference

Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.

Support model development, with an emphasis on auditability, versioning, and data security

Hands-on experience using tools such as: Python, TensorFlow, Keras, PyTorch, C/C++, and databases.

Experience supporting efforts training and deploying machine learning models.

Proven experience implementing CI/CD on large-scale operational AI pipelines.

Operational experience deploying across cross-provider cloud computing.

You have previous experience working on production AI systems

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