Build and maintain machine learning models for various applications, such as natural language processing, computer vision, and recommendation systems
Perform exploratory data analysis (EDA) to identify patterns and trends in data
Clean, preprocess, perform hyperparameter tuning and analyze large datasets to prepare them for AI/ML model training
Build, test, and optimize machine learning models and experiment with algorithms and frameworks to improve model performance
Use programming languages, machine learning frameworks and libraries, algorithms, data structures, statistics and databases to optimize and fine-tune machine learning models to ensure scalability and efficiency
Learn to define user requirements and align solutions with business needs
Work on AI/ML engineering projects, perform feature engineering and collaborate with teams to understand business problems
Learn best practices in data / AI/ML engineering and performance optimization
Contribute to research papers and technical documentation
Contribute to project documentation and maintain data quality standards
Requirements
BSc/MSc/PhD in computer science, data science or related discipline with 1+ years of industry experience building cloud-based ML solutions for production at scale
Good problem solving skills, for both technical and non-technical domains
Good broad understanding of ML and statistics covering standard ML for regression and classification, forecasting and time-series modeling, deep learning
3+ years of hands-on experience building ML solutions in Python, incl knowledge of common python data science libraries (e.g. scikit-learn, PyTorch, etc)
Hands-on experience building end-to-end data products based on AI/ML technologies
Some experience with scenario simulations
Experience with collaborative development workflow: version control (we use github), code reviews, DevOps (incl automated testing), CI/CD
Team player, eager to collaborate and good collaborator
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