Senior Machine Learning Engineer

Company Details

State-of-the-art technologies to aerospace. We specialize in parts and systems for space and hi-rel applications, including microelectronics, mechanisms, electronics and robotics

ARQUIMEA is a cross-sectorial international technology group, which develops innovative solutions and products in sectors with high demand activity. We cover industries as varied as aerospace, security and defense, manufacturing, health, finance, or agriculture; in all of them, with a focus on disruptive technologies. Some of our main products are the Quantum ASIC ARQ-RSB01/2 chips, the Hold-Down & Release Mechanisms (HDRM) for commercial satellites, falcon-shaped UAVs for airport safety, or collaborative robots for Industry 4.0. We work with companies which are referent in their sectors, such as Altair, the European Space Agency (ESA) or ANDRA.

ARQUIMEA Research Center (ARC) was born in 2019 with the aim of inventing the technologies of tomorrow. We focus on Deep Tech solutions with a very high impact on the markets and/or future global challenges. We rely on a product-oriented strategy, market diversification and internationalization to achieve a sustainable growth with the aim of creating the technology of tomorrow. Our projects arise from the convergence of exponential technologies or Deep Tech: Nanotechnology and Materials, Sensors, Drones & Robotics, Biotechnology & Genetics, Artificial Intelligence (AI), Quantum Technologies, Networks & Security, Digital Manufacturing, and Blockchain & Crypto.

ARC AI & Data Science conducts research in and apply Machine Learning (ML) and Deep Learning (DL) techniques, methods, and tools. We organize in project-specific interdisciplinary teams with researchers and engineers from disciplines ranging from media and entertainment, robotics, cybersecurity, and quantum technologies to life sciences, biotech and fintech. We comprise ML engineers, ML researchers, data scientists and software engineers, with a passion for AI and DL research and technology, and expertise in the following areas: computer vision, neural rendering, implicit neural representations, time series forecasting, DNN model compression, affective computing, and AI safety.


  • Work with other ML engineers, ML researchers, data scientists and software engineers, to develop outstanding AI technology.
  • Study and apply state-of-the-art concepts, methods and tools proposed in major ML/DL scientific forums (e.g., ICCV, CVPR, NeurIPS, ICML, ICLR) and journals.
  • Test and adapt open-source code implementing state-of-the-art concepts, methods, and techniques.
  • Design, train, verify and validate, deploy, and operate efficient, reliable, and scalable ML models, leveraging
  • Co-lead AI research projects in computer vision, natural language processing, automated speech recognition, or any other ML/DL topic.
  • Bring ML/DL capabilities to interdisciplinary agile research teams, collaborating with researcher and engineers from other disciples, following an agile methodology.
  • Carry out technology scouting to identify and validate state-of-the-art technologies able to provide at least a 10x impact on the markets and/or future global challenges.


  • MSc or PhD. in Computer Science, Mathematics, Telecommunications, or Electronics.
  • Strong computer science fundamentals, algorithms, and data structures background.
  • +2 years’ experience programming experience in Python.
  • Strong knowledge of ML/DL fundamentals and techniques.
  • Proven experience in applied ML/DL; computer vision, natural language processing, and/or audio processing is a plus.
  • +2 years’ experience working with any of the following ML/DL frameworks: Tensorflow, Pytorch.
    Docker containers.
  • Deployment of services in cloud-native (i.e., Kubernetes) and/or public cloud infrastructure (AWS, Azures or GCP).
  • +2 years’ experience working in agile teams following SCRUM or KANBAN.

Should you have some of the following, it will help you stand out

  • Processes and applications of artificial perception in robotics (UGV and/or UAV).
  • Development of AI proofs of concept (PoC) and/or prototypes in R&D projects.
  • GPU programming (CUDA or OpenCL), parallel programming.
  • Contribution to research communities, including publication in major ML/DL scientific forums (e.g., ICCV, CVPR, NeurIPS, ICML, ICLR) and/or journals.
  • Contribution to open-source projects.
  • Previous experience working in start-ups.

Tagged as: Kubernetes, scrum, kanban, pytorch, tensorflow

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