Senior Machine Learning Engineer/Scientist

Construction impacts our daily lives in unique ways. The industry shapes the cities we live in and afterward, our cities shape us, by producing the homes we live in and the infrastructure that drives our economies. With 200,000 people a day globally moving to urban areas, the industry must respond to some of the biggest challenges of our time, but it is plagued by waste and inefficiency. At Scaled Robotics we are applying robotics and machine learning to build new tools that can track, analyze and optimize construction processes.

Located in Barcelona (near the beach), our multifaceted team of experts in robotics, mathematics, computer science, engineering, and architecture is working to move the construction industry forward. To achieve this goal, we are looking for people who want to be part of our tight-knit team and are as passionate as we are about creating something that can transform this industry.

We have built a unique work environment that is innovative, open, and collaborative, where we value the ability to learn and grow

As a Senior Machine Learning Engineer, you will apply quantitative analysis, machine learning and other statistical methods to understand and improve our products that help optimize our clients' construction projects. In collaboration with our vision and robotics teams, you will actively contribute to key company projects in 2D/3D recognition, semantic segmentation, time series analysis, etc.

Your responsibilities ​​

  • Collaborate with cross-functional teams to analyze and improve our users' experience

  • Apply machine learning, computer vision, and deep learning algorithms to extract insights from our data sets

  • Maintain ML and data pipelines and continuously improve internal ML models with insights from latest published research and state of the art.

  • Implement prototypes to demonstrate potential value and validate ideas

  • Communicate the insights and help develop the product, with the rest of R&D and product teams


You must have​

  • Ph.D. in Computer Science, Mathematics, Statistics, Physics or related fields

  • Strong quantitative skills (statistics, probability, machine learning) as well as knowledge of algorithms/data structures

  • 3+ years experience as a Machine Learning/Data Scientist (at least 2 years in non-academic positions)

  • Experience setting up and maintaining production data pipelines. Deploying ML models as micro-services

  • Strong software development skills (Python, C++)

  • Some industry experience in at least one of the following fields: computer vision, applied statistics

Nice to have​

  • Strong knowledge of the theory and practice of controlled experiments

  • Experience with a deep learning framework (Keras, TensorFlow, etc..)

  • Advanced knowledge of Computer Vision and 3DV Vision algorithms

  • Publication in top tier conferences CVPR, ICCV, NIPS, ICML, 3DV, etc

  • Familiarity with building and deploying data pipelines and services in AWS


  • Competitive salary and stock options

  • Flexible schedule and the possibility of working from home.

  • Potential opportunities to travel around Europe and Internationally

  • Modern stylish office in Poble Nou with fully stocked kitchens

  • Team-building activities

  • Language and other courses

Scaled Robotics in the last 6 months​

We strongly encourage women and minorities to apply.

We are looking to build a strong team that has a diversity of race, gender, sexual orientation, religion, ethnicity, national origin and all the other fascinating characteristics that make us different. Our vision for Scaled Robotics is to build a work environment where a diverse mix of talented people want to come, to stay, to learn, do their best work and grow along with the organization. We pride ourselves on being at the forefront of innovation in construction robotics and we know our company runs on the hard work and dedication of our passionate and creative employees.

When applying address the application to Bharath and let me know why you want to join our team.

Apply directly to