Machine Learning Engineer, Deep Learning, NLP, LLMs
Pro Talent
AWSAzureCloudGoogle Cloud PlatformNumpyPandasPythonPyTorchScikit-LearnTensorflow
Job Level
SeniorLead
Tech Stack
Amazon RedshiftAWSCloudETLKubernetesPythonPyTorchScikit-LearnSQLTensorflow
About the role
- Turn experimental ML research and prototypes into scalable, maintainable production systems.
- Position based in Kyiv or Lviv, Ukraine; team primarily works remotely with occasional in-person meetings in the Kyiv office.
- Collaborate closely with data scientists to turn research and prototypes into reliable, production-ready solutions.
- Develop and maintain scalable pipelines that power data, feature, and model workflows across the organization.
- Ensure solutions are efficient, reproducible, and maintainable, supporting long-term use and growth.
- Monitor and troubleshoot deployed systems, optimizing performance and reliability over time.
- Apply software engineering best practices, including testing, automation, version control, and deployment processes.
- Contribute to a growing team, helping to improve workflows and support the adoption of data-driven solutions.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.
- 7+ years of professional experience in Data Science Engineering, or in software engineering roles with significant exposure to data science workflows.
- Proficiency in Python, with experience developing clean, maintainable, and production-ready code.
- Proficiency in SQL and relational databases, for working with large-scale datasets.
- Solid understanding of software engineering best practices, including version control, testing, and containerization.
- Ability to troubleshoot complex problems, take ownership of solutions, and quickly learn new tools or technologies.
- Strong collaboration and communication skills, able to work effectively with a growing Data Science team.
- Comfortable communicating and coordinating with U.S.-based colleagues.
- Ability to work 11 am - 8 pm EEST.
