Machine Learning Engineer

We are seeking a passionate and skilled **Machine Learning Engineer** to join our forward-thinking team.

As a Machine Learning Engineer, you will be responsible for designing, developing, and deploying machine learning models that drive key business decisions and enhance our product offerings. You will work closely with data scientists, data engineers, and software developers to integrate machine learning solutions into our existing systems.

**Key Responsibilities**:

- **Model Development**: Collaborate with data scientists to design and implement models that address business and product needs.
- **Model Deployment**: Develop and maintain infrastructure for deploying models into production, ensuring scalability and reliability.
- **Data Processing**: Work with data engineers to ensure data is clean, well-structured, and accessible for model training and evaluation.
- **Performance Optimization**: Continuously monitor and optimize model performance, implementing improvements as necessary.
- **Collaboration**: Work closely with cross-functional teams to integrate machine learning solutions into products and services.
- **Evolution**: Learn about our ML Platform and help the team to keep improving and growing.

**Qualifications**:

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 2+ years of experience in machine learning or a related field, not focused in the science layer, more on the technical one.
- Proficiency in programming languages such as Python.
- Experience with machine learning frameworks and libraries (e.g., MLflow mainly if possible, but can be TensorFlow, PyTorch).
- Familiarity with cloud platforms (e.g., AWS, GCP) and containerisation technologies (e.g., Docker, Kubernetes).
- Strong problem-solving skills and the ability to work collaboratively in a team environment.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.

**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: L3 [Up to 55K gross annually]
- 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 (but we have remote positions).- 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

**¿Por qué Cabify?**:
**Híbrido y flexible, a tu medida**:

- Disfruta de la flexibilidad de nuestro modelo híbrido: trabaja 2 días desde casa y 3 en la oficina, con la posibilidad de teletrabajar 6 semanas al año. Queremos que encuentres el equilibrio perfecto entre la comodidad del hogar y la dinámica del trabajo presencial.

**Desarrollo contínuo**:

- Tienes a tu disposición programas y herramientas especiales para una formación personalizada que te permitirán desarrollarte y estar en aprendizaje contínuo.

**Beneficios que marcan la diferencia**:

- Disfruta de crédito en la app para movilizarte a donde quieras y aprovecha los 10 viernes libres que tenemos al año para recargar energías.