Staff Machine Learning Engineer

Role Overview

• 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
• Participates in learning activities around modern software design, machine learning, and development core practices (communities of practice)
• Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations
• Attends conferences and learns how to apply new innovations and technologies where appropriate
• Researches and analyzes business trends and behavioral data to identify opportunities for improvement and new initiatives
• Leads the evaluation development and recommendation of specific technology products and platforms to provide cost-effective solutions that meet business and technology requirements
• Researches and designs best fit infrastructure, network, database, security, and machine learning architectures for products
• Proactively creates and maintains tools for monitoring and support
• Participates in project planning and management across multiple efforts
• Develops formal training courses
• Fields questions from other product teams or support teams
• Monitors tools and participates in conversations to encourage collaboration across product teams
• Provides application support for software running in production
• Proactively monitors production Service Level Objectives for products
• Proactively reviews the Performance and Capacity of all aspects of production: code, infrastructure, data, message processing, and prediction quality

Requirements

• 3
• 6 years of relevant work experience
• 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
• Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc
• Experience in a modern scripting language (preferably Python)
• Experience in modern web application framework such as Node.js
• Experience in a front-end technology and framework such as HTML, CCS, JavaScript, ReactJS, D3
• Experience in writing SQL queries against a relational database
• Experience in version control systems (preferable Git)
• Experience in a Linux or Unix based environment
• Experience in a CI/CD toolchain
• Experience in REST and effective web service design
• Experience in production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security
• Experience in NoSQL databases
• Experience in cloud computing platform and associated automation patterns and machine learning services they provide
• Experience in defensive coding practices and patterns for high Availability
• Experience in A/B testing and effective REST design for scalable web services architecture
• Familiarity with advanced machine learning architectures GANs, GRU, LSTMs, RNNs, CNNs, style transfer.

Tech Stack

• BigQuery
• Cloud
• D3.js
• Google Cloud Platform
• JavaScript
• Linux
• Node.js
• NoSQL
• Pandas
• Python
• PyTorch
• React
• Scikit-Learn
• SQL
• Tensorflow
• Unix

Benefits

• Health insurance
• 401(k) matching
• Flexible work hours
• Professional development opportunities