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What you will accomplish:
Designing, developing, and researching Machine Learning systems, models
Studying, transforming, and converting data science prototypes
Searching and selecting appropriate data sets before performing data collection and data modeling
Performing statistical analysis and using results to improve models
Training and retraining machine learning systems and models as needed, monitor quality of the models in production
Identifying differences in data distribution that could affect model performance in real-world situations
Visualizing data for deeper insights
Analyzing the use cases of machine learning algorithms and ranking them by their success probability
Enriching existing machine learning frameworks and libraries
Verifying data quality and/or ensuring it via data cleaning
What you will bring:
Proven experience in building machine learning models in computer vision or natural language processing related fields
Experience in modern ML tooling related to experiment management, containerization, orchestration, processing pipelines and data version control
Experience in bringing ML models in production, monitoring and maintaining them throughout their entire life cycle. Familiarity with DevOps and MLOps cultures
Proficient in Python for scripting and data manipulation tasks and software development best practices
Proficient in SQL for querying and managing databases
Strong analytical and problem-solving skills
Fluent spoken and written English
What Sets You Apart:
Proven track record in leading multi-functional teams and collaborating effectively with partners at different levels of the organization
Experience with PyTorch, Google Cloud, Kubeflow, AirFlow, ElasticSearch
A coaching & knowledge sharing mindset
Experience in working with crowdsourcing approaches for collecting datasets
Experience in mentoring junior positions and collaboration with data analytics or data engineers on the projects
Experience in working remotely
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