The Staff Machine Learning Engineer is responsible for joining a product team and contributing to the software design, algorithm design, and overall product lifecycle for a product that our users love.
Requirements
- Experience to algorithms such as clustering, forecasting, anomaly detection, and neural networks.
- Experience to basic statistics and regression algorithms
- Experience in advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and embeddings generation and utilization
- Experience in training machine learning models with extremely large datasets
- Experience with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc.
- Experience with GPU acceleration (i.e. CUDA and cuDNN)
- Experience in Google Cloud Platform and AI/ML related components such as Vertex AI, BigQueryML, and AutoML
Responsibilities
- Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions
- Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable
- Configures commercial off the shelf solutions to align with evolving business needs
- Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively
- Researches and designs best fit infrastructure, network, database, security, and machine learning architectures for products
- Proactively creates and maintains tools for monitoring and support
- Provides application support for software running in production
Other
- The engineering process is highly collaborative.
- Staff ML Engineers are expected to pair daily as they work through user stories and support products as they evolve.
- The role could interface with Business Stakeholders, Technology Infrastructure teams, and Development teams to ensure that business requirements are properly met within a machine learning solution.
- Staff ML Engineers will be a core player on the product team and are expected to build and grow skillsets of more junior engineers.
- Typically requires overnight travel 5% to 20% of the time.
