Position Purpose
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. 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.
ML Engineers may be involved in designing and implementing AI/ML algorithms to embed directly into software products. Activities may include using specific HD process techniques, integration, design, and development. 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. The role may also be involved in performance tuning, testing, and product monitoring. Other responsibilities may include performing customer outreach, designing ML educational material, and data engineering.
Staff ML Engineers will be a core player on the product team and are expected to build and grow skillsets of more junior engineers. You will also be able to drive multiple ML initiatives by directing algorithm and technology product design.
Major Tasks, Responsibilities & Key Accountabilities
- 45% Delivery and Execution - 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.
- 15% Learning - 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.
- 20% Strategy and Planning - 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.
- 20% Support and Enablement - 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.
Standard Minimum Qualifications
- Must be eighteen years of age or older.
- Must be legally permitted to work in the United States.
Education Required
The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.
Years Of Relevant Work Experience
3 years
Preferred Qualifications
- 3 - 6 years of relevant work experience
- Experience with algorithms such as clustering, forecasting, anomaly detection, and neural networks.
- Experience with 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.
Knowledge, Skills, Abilities And Competencies
- Global Perspective
- Manages Ambiguity
- Nimble Learning
- Self-Development
- Collaborates
- Cultivates Innovation
- Situational Adaptability
- Communicates Effectively
- Drives Results
- Interpersonal Savvy