Software Engineer, Machine Learning

hace 5 días


Madrid, Madrid, España Cabify A tiempo completo

Do you want to change the world? At Cabify, that's what we're doing. We aim to make cities better places to live by improving mobility for the people living in them, connecting riders to drivers at the touch of a button. Maybe one day cities will be places where nobody needs a private car. But we've still got a long way to joining us?

About the position

We are seeking a passionate and skilled Software Engineer, Machine Learning, to join our team. In this role, you will bridge the gap between software engineering and data science, architecting the systems that allow our machine learning capabilities to scale. You will work closely with cross-functional teams to build robust infrastructure and integrate complex ML solutions into our production environment.

Key Responsibilities
  • Collaboration in Model Development: Work hand-in-hand with data scientists to understand their needs and assist in the implementation of machine learning models.
  • System Architecture & Scalability: Architect efficient and scalable systems that drive complex ML applications. You will move beyond simple model deployment to building the backbone infrastructure that supports high-throughput training and inference.
  • Model Optimization: Monitor and optimize the performance of models in production, implementing improvements from a software engineering perspective.
  • API Development: Assist in the creation of APIs that facilitate the integration of models into our existing systems, ensuring optimal performance.
  • Platform Evolution: Lead technical efforts to improve our ML Platform (Lykeion). You will identify performance bottlenecks, resolve scalability issues, and introduce new technologies (e.g., containerization updates, new CI/CD patterns) to keep our stack modern.
  • Effective Communication: Act as a bridge between data scientists and the engineering team, ensuring fluid and effective communication.
Qualifications
  • Degree in Computer Science, Engineering, or a related field.
  • More than 2 years of experience in technical machine learning roles, with an emphasis on software engineering.
  • Proficiency in programming languages such as Python.
  • Experience with machine learning frameworks and libraries (e.g., MLflow, TensorFlow, PyTorch) is a plus.
  • Familiarity with cloud platforms (AWS, GCP) and containerization technologies (Docker, Kubernetes). Experience in using and deploying applications with Kubernetes is required.
  • Strong problem-solving skills and ability to work in a team.
  • Excellent communication skills to explain complex technical concepts to non-technical audiences.
What We Offer

We're a company full of motivated people and we never want that to change. Here are some more reasons why it rocks to be part of our high-performance team.

Excellent Salary conditions: 39K - 55K

A collaborative and innovative environment where your contributions make a real impact

Opportunities to work on cutting-edge projects and advance your career in machine learning

Continuous learning and development opportunities to enhance your expertise in machine learning

Recharge days (10 Free Fridays annually)

Our office is located in Madrid

  • Flexible work environment & hours

  • 3 weeks full remote six-monthly

Regular team events

Cabify staff free rides

Personal development programs based on our career paths

Coursera: your own license in Coursera to take as many courses as you wish and continue developing your skills

At Cabify, diversity fuels our Product & Engineering teams. We actively recruit talent beyond traditional channels, embracing individuals from diverse backgrounds and supporting initiatives like Women Tech Dating, Contrata Diferente and our Internal Diversity Committee. Our commitment is reflected in inclusive job descriptions, creating an environment where every contribution is cherished. Join Cabify to be part of innovative teams that truly represent the rich tapestry of talent in the tech industry.

Join us



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