Role overview
Machine Learning Engineer (Contractor)
Remote
Part-time
*Pay attention: only those candidates who meet the listed requirements will receive an answer!
Location**
Ukraine
Necessary skills and qualifications
Minimum of 3 years in a Data Scientist or Machine Learning Engineer role
An academic degree in Data Science, Computer Science, or a closely related technical field
Solid understanding of the full ML lifecycle, including problem framing, feature engineering, training, validation, and production deployment
Strong skills in data preprocessing, normalization, feature engineering, and general data engineering practices
Advanced knowledge of NumPy, Pandas, Matplotlib, and related libraries
Practical expertise with ML libs: Scikit-learn, XGBoost, SciPy, librosa, etc.
Skilled in working with both relational and non-relational DBs
Competence in building services using FastAPI or Flask for backend service development
Upper-intermediate level of English proficiency
Proficiency in using Git for version control and collaboration
Will be a plus
Background in audio data processing
Hands-on experience with AWS cloud services
Integration of algorithms or models into embedded systems
Familiarity with ClickHouse
Responsibilities
Build and maintain scalable, production-grade data pipelines for audio processing flows
Implement an algorithm for finding similar music in a database
Provide algorithm tuning after QA and client feedback
Establish algorithm evaluation, versioning, and deployment workflows
Integrate implemented ML algorithms into the project
Work cross-functionally with engineers, embedded engineers, cloud engineers, and business teams to deliver end-to-end ML solutions aligned with business needs
What you'll work on
Build and maintain scalable, production-grade data pipelines for audio processing flows
Implement an algorithm for finding similar music in a database
Provide algorithm tuning after QA and client feedback
Establish algorithm evaluation, versioning, and deployment workflows
Integrate implemented ML algorithms into the project
Work cross-functionally with engineers, embedded engineers, cloud engineers, and business teams to deliver end-to-end ML solutions aligned with business needs
What we're looking for
An academic degree in Data Science, Computer Science, or a closely related technical field
Solid understanding of the full ML lifecycle, including problem framing, feature engineering, training, validation, and production deployment
Strong skills in data preprocessing, normalization, feature engineering, and general data engineering practices
Advanced knowledge of NumPy, Pandas, Matplotlib, and related libraries
Practical expertise with ML libs: Scikit-learn, XGBoost, SciPy, librosa, etc.
Skilled in working with both relational and non-relational DBs
Competence in building services using FastAPI or Flask for backend service development
Upper-intermediate level of English proficiency
Proficiency in using Git for version control and collaboration