Senior Machine Learning Engineer

Job Description

Collaborates with product team members (UX, engineering, and product management) to develop secure, reliable, scalable machine learning solutions. Documents, reviews, and ensures adherence to quality and change control standards. Works with the Product Team to create developer-ready, easy-to-understand, and testable user stories. Writes custom code or scripts to automate infrastructure, monitoring services, and test cases. Performs "destructive testing" to ensure production resiliency. Configures commercial off-the-shelf solutions to meet evolving business needs. Creates dashboards, logging, alerting, and responses to proactively capture and address issues. Participates in learning activities around modern software design, machine learning, and development practices. Stays updated on new technologies and best practices. Addresses questions from other product teams or support teams. Monitors tools and encourages collaboration across product teams. Provides application support for software in production. Monitors production Service Level Objectives and reviews the Performance and Capacity of all production aspects.

Qualifications

1. 2-4 years of experience in a relevant role. 2. Knowledge of algorithms such as clustering, forecasting, anomaly detection, and neural networks. 3. Understanding of basic statistics and regression algorithms. 4. Proficiency with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc. 5. Experience with Google Cloud Platform and AI/ML related components such as Vertex AI, BigQueryML. 6. Understanding of effective data engineering practices and big data platforms such as BigQuery, Data Store. 7. Expertise in a modern scripting language (preferably Python). 8. Knowledge with GPU acceleration (i.e., CUDA and cuDNN). 9. Familiarity with modern web application frameworks such as Node.js. 10. Proficiency in front-end technologies and frameworks such as HTML, CCS, JavaScript, ReactJS, D3. 11. Skill in writing SQL queries against a relational database. 12. Familiarity with version control systems (preferably Git). 13. Experience in a Linux or Unix-based environment. 14. Familiarity with CI/CD toolchains. 15. Experience with REST and effective web service design. 16. Understanding of production systems design, including High Availability, Disaster Recovery, Performance, Efficiency, and Security. 17. Knowledge of NoSQL databases. 18. Understanding of cloud computing platforms and associated automation patterns and machine learning services. 19. Familiarity with defensive coding practices and patterns for high availability. 20. Knowledge of A/B testing and effective REST design for scalable web services architecture. 21. Familiarity with advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and embeddings generation and utilization.

Benefits

- Competitive salary - Health insurance - 401(k) matching - Flexible work hours - Paid time off - Remote work options