• At least 4 years of experience in software development
• 2+ years of experience in ML
• Experience with NLP
• Strong track record delivering high-quality Python code
• Practical experience developing, training and debugging Keras and Tensorflow models
• Experience with: Tensorflow, Keras
• Experience with modern software testing methodologies
• Fundamental knowledge of statistics, probability theory and mathematics
• Intermediate English (written and verbal)
• Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field
• Natural language processing
• Docker and Kubernetes
• CI/CD
• Google AI platform
Why work with us?
• Life at Waverley means collaborating with dedicated professionals, passionate about technology
• Our people demonstrate outstanding engineering culture through constant learning and knowledge-sharing
• We value Responsible Freedom, which means we evaluate the results and have flexibility in work style or locations
We offer:
• A chance to contribute to the cutting edge of Silicon Valley software development
• Possibility to work in a startup-like atmosphere, in a new and growing team
• Modern office, comfortable work environment, the best tools
• Competitive compensation
• Friendly inspiring atmosphere
• Develop infrastructure for training, evaluating and deploying ML models
• Design internal data analysis tools
• Develop custom ML/NLP models and algorithms
• Evaluate state-of-the-art ML/NLP models on internal datasets
About the client:
Our client develops an
Position description:
Our client is looking for a savvy Machine Learning Engineer to join our growing team of analytics experts. The hire will be responsible for implementing and maintaining our data pipeline, building infrastructure for training and evaluating ML models as well as internal tools for data analysis. The ideal candidate has experience productizing Keras and Tensorflow models and delivering high-quality, efficient and maintainable Python code. The Data Engineer will work closely with our Machine Learning Scientists to ensure optimal data pipeline architecture.