Computer Vision Engineer

newrole; Donostia/San Sebastián; Presencial; EUR 55.000 - 75.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive salary

Global career path

Tailored trainings

International environment

Descripción de la vacante

newrole is building an eco-system for trusted online education by applying computer vision and deep learning to verify identities and protect integrity. You will join our AI team to enhance and extend CV/ML capabilities in a fast-paced environment.

You'll work on feature creation, model training, and production deployment, collaborating across teams to push the boundaries of technology in education. Remote-friendly, growth-focused culture.

Formación

• Specific training in Computer Vision and Deep Learning.

Responsabilidades

• Formulate innovative approaches to combat fraud using computer vision and machine learning.
• Create new features, train new models, deploy them into production environment.
• Contribute by extending and improving our ML frameworks and platform, creating next-generation capabilities.
• Build and deploy solutions to interesting computer vision or machine learning problems including document data extraction, fraud detection or biometric verification challenges. Design and implement efficient pre-processing steps around digital images or video files.
• Work alongside other machine learning and computer vision specialists in order to deliver on both short term objectives and long term goals.
• Support and guide other engineers in learning about, applying and delivering product features driven by machine learning techniques.

Conocimientos

Computer Vision

Deep Learning

Python

AWS

PyTorch

OpenCV

Startup experience

Herramientas

AWS (Lambda, Sagemaker)

Descripción del empleo

Our client is on a mission to build trust in online learning. So they will enable people to access quality education 100% online and as a consequence access to new opportunities that can improve your quality of life.

Online education is growing, but with it, some common problems are arising across the industry: teachers and evaluators do not trust to evaluate online.

How can organizations avoid online fraud? How can organizations verify that a user was actually the one who took the online exam or actually acquired the required skills in the online course?

Our client was born with the aim of helping organizations improve the quality assurance of their online evaluations. They have developed a system and method of authentication and continuous monitoring of the user in an online service using multibiometry.

How is our people?

They are the ones who make this happen and the core of the company. They make this company a reality, making a global impact and building the future of education.

What drives they?

They're a growing company with happy and motivated people, working on an impactful product in a fast-paced environment. They are driven with the following values - 3BDAS:

Be positive: Practice positivity: look for solutions, expecting good results and success. Acknowledge bad results or experiences, learn from them, do better.

Be collaborative: Constructively explore ideas with others to search for solutions that extend one's limited vision (communicate, visualize and acknowledge).

Build trust: By being honest and supportive, actively listening, being consistent, collaborating across teams and functions, and taking responsibility for your acts and words.

Dare to commit: Decide to show up fully and consistently while seeing things to their logical or necessary conclusion. Make things work.

Always go beyond your limits: Through self-awareness, curiosity and initiative. With determination, discipline and DOING.

Stay Agile: Be able to quickly adapt or evolve in response to changing circumstances in a highly responsive way so that we deliver our service to meet and exceed customer expectations and in a timely manner.

Position Summary

Are you someone who likes a challenge and wants to take responsibility? You will be part of our amazing AI team with the aim of improving and enhancing our Computer Vision algorithms or creating new ones giving answer to existing and new challenges. In addition to that, you will work with other technologíes such as audio analysis or NLP.

Responsibilities

• Formulate innovative approaches to combat fraud using computer vision and machine learning.
• Create new features, train new models, deploy them into production environment.
• Contribute by extending and improving our ML frameworks and platform, creating next-generation capabilities.
• Build and deploy solutions to interesting computer vision or machine learning problems including document data extraction, fraud detection or biometric verification challenges. Design and implement efficient pre-processing steps around digital images or video files.
• Work alongside other machine learning and computer vision specialists in order to deliver on both short term objectives and long term goals.
• Support and guide other engineers in learning about, applying and delivering product features driven by machine learning techniques.

Desired skills

• Specific training in Computer Vision and Deep Learning.
• 3+ years of experience in Computer Vision and Deep Learning, ideally around 5.
• Experience working in investigation or start-up environment.
• AWS knowledge (Lambda, Sagemaker, Rekognition...).
• Python development experience and good practices.
• Knowledge of libraries such as pytorch and opencv.

Social Impact driven: enabling access to quality education through online learning, which is linked to the Sustainable Development Goals (SDG) 4. Access to Quality Education and 13. CO2 reduction. How do we measure it?

• Competitive salary, commission and attractive benefits
• Global career path for specialists and leadership
• Tailored trainings and development opportunities
• International and inspirational working environment with a dynamic work culture

Objective 1: Strengthen the quality of online training.

Indicator 1: number of online training users who have validated a professional

degree or certification.

Objective 2: Improve accessibility to higher education or corporate training

Indicator 1: Number of users with disabilities who have been able to examine themselves remotely.

Indicator 2: Number of users in areas far from the training centers who have been able to examine themselves remotely.

Indicator 3: Number of users with time restrictions who have been able to examine themselves remotely.

Indicator 4: Number of users with financial restrictions who have been able to examine themselves remotely.

Objective 3: Reduce the environmental impact of trips to educational centers or corporates

Indicator 1: C02 emissions avoided thanks to remote examinations

Join the revolution and build the future of education