MACHINE LEARNING ENGINEER II (REMOTE)

Req188389

Position Purpose

The Machine Learning Engineer II 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. 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.

ML Engineers should be able to operate independently with minimum guidance from others, although will typically work as part of a team with varying skill levels to create, support, and deploy production applications. This role will review submitted code and provide feedback to improve, based on best practices.

Key Responsibilities

• 65% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions; Documents, reviews, and ensures that all quality and change control standards are met; Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Writes custom code or scripts to automate infrastructure, monitoring services, and test cases; Writes custom code or scripts to do "destructive testing" to ensure adequate resiliency in production; Program configuration/modification and setup activities on large projects using HD approved methodology; 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
• 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

Direct Manager/Direct Reports

• This Position typically reports to Software Engineer Manager or Sr Software Engineer Manager
• This Position has 0 Direct Reports

Travel Requirements

• Typically requires overnight travel 5% to 20% of the time.

Physical Requirements

• Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.

Working Conditions

• Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

Minimum Qualifications

• Must be eighteen years of age or older.
• Must be legally permitted to work in the United States.

Preferred Qualifications

• 2+ years of experience in Machine Learning, Data Science, Software Engineering, or a related field
• Experience developing, training, and deploying machine learning models in production environments
• Hands-on experience with ML frameworks and tools such as Python, Scikit-learn, TensorFlow, PyTorch, Pandas, and Jupyter Notebooks
• Experience with feature engineering, model evaluation, experimentation, and monitoring
• Knowledge of machine learning techniques including classification, regression, clustering, forecasting, and anomaly detection
• Experience working with cloud-based ML platforms, preferably Google Cloud Platform (GCP), Vertex AI, and BigQuery
• Strong SQL and Python skills with experience working on large datasets
• Familiarity with MLOps, CI/CD pipelines, Git, and Linux/Unix environments
• Experience building and consuming REST APIs and integrating ML solutions into applications
• Understanding of software engineering best practices, scalability, reliability, and system performance
• Exposure to deep learning, NLP, Generative AI, or LLM-based solutions is a plus
• Experience with A/B testing and data-driven decision making

Minimum Education

• The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.

Preferred Education

• No additional education

Minimum Years Of Work Experience

• 1

Preferred Years Of Work Experience

• No additional years of experience

Minimum Leadership Experience

• None

Preferred Leadership Experience

• None

Certifications

• None

Competencies

• Global Perspective
• Manages Ambiguity
• Nimble Learning
• Self-Development
• Collaborates
• Cultivates Innovation
• Situational Adaptability
• Communicates Effectively
• Drives Results
• Interpersonal Savvy