Machine Learning Engineer

Responsibilities

• Perform as a hands-on team lead, both developing code and leading a team (50% each).
• Take ownership of multiple projects end to end.
• Provide guidance to the team on Client techniques, evaluation of tools and platforms.
• Lead troubleshooting efforts in production.
• Develop Client solutions to business problems.
• Participate in the Client R&D program to develop prototypes and POCs for emerging technologies.

Required Skills

• Familiarity with software engineering best practices in an Agile environment.
• Ability to build tools to extracting useful information from, label and analyze video data.
• An understanding of the computational trade-offs needed for real-time machine learning applications.
• Knowledge of AWS infrastructure is a plus.
• Familiarity with libraries/packages/APIs (e.g. scikit-learn, Keras, PyTorch, TensorFlow, etc).
• Familiarity with linux/unix Familiarity with different ML models (decision trees, random forests, support vector machines, neural networks, nearest neighbor, ensemble of multiple models, etc.).
• Familiar with ML Experiment at scale, ML experiment artifacts management and Machine Learning model deployment.

Required Experience

• 3+ years as a Machine Learning Engineer
• 2+ years of experience using some combination of Python and/or C++.
• Experience with ML models deployed in a production environment.
• Experience with natural language processing.
• Experience leading data science teams.

Education Requirements

• Bachelor’s Degree in Computer Science, Computer Engineering or a closely related field.