Are you driven by the challenges of data and excited about transforming machine learning models from prototype to production in dynamic environments?
Do you thrive on using data to create strategic insights and optimizing full ML pipelines?
We are looking for experienced Data Scientists and MLOps Engineers to join our client’s team in Barcelona, Warsaw, or Virginia, and collaborate with an innovative tech startup focused on accelerating growth for mobile app businesses worldwide.
This is a fully remote role! Enjoy the flexibility to work from anywhere while collaborating with a dynamic, mission-driven team across various time zones. Every quarter, we gather in Barcelona for in-person workshops, giving you a chance to connect with the team face-to-face. It’s an ideal opportunity if you´re based outside!
Push the boundaries of data science and MLOps, transforming data insights into production-ready solutions for a global impact!
Tasks

- Conduct in-depth data analysis, developing insights and models that drive ad-tech performance and campaign analytics

- Develop and deploy scalable data science and MLOps solutions from model design to production, enhancing performance, ROI, and ad targeting

- Design, implement, and manage MLOps and CI/CD pipelines on cloud platforms (primarily AWS)

- Provision and maintain AWS infrastructure for machine learning, utilizing tools like Terraform and CloudFormation

- Oversee model lifecycle management and large-scale ML challenges, including distributed training and high-load environments

- Collaborate with cross-functional teams to translate business needs into data-driven strategies, ensuring model accuracy, efficiency, and scalability

- Monitor, update, and enhance existing machine learning models to stay responsive to market trends and security requirements


Requirements

- Bachelor’s or Master’s degree in Computer Science, Statistics, or a related field

- 3+ years of experience in Data Science or MLOps, with a solid understanding of ad-tech environments

- Proficiency in Python, SQL, and ML libraries (e.g., sci-kit-learn, PyTorch, TensorFlow)

- Experience with AWS services, including MLOps tools like SageMaker, Kubeflow, and MLFlow

- Strong knowledge of DevOps principles, CI/CD, cloud platform infrastructure, and data security

- Excellent collaboration and communication skills for cross-functional teamwork

- Great plus! if you have: Knowledge of additional cloud platforms (GCP, Azure), Docker, Kubernetes, or Snowflake, familiarity with high-load systems and vector databases, certifications in machine learning or cloud computing