Principal Machine Learning Engineer
About the role
This role involves implementing, deploying, and maintaining machine learning models in production. It requires expertise in model development, performance monitoring, and collaboration with various stakeholders.
Responsibilities
Model Productionization: Implements ML models for production, collaborates with stakeholders to make technical decisions, and ensures models are ready for deployment.
Model Deployment: Ensures ML models are ready for deployment, automates workflows, and monitors model performance.
Data Quality: Evaluates data quality, security, and privacy issues and minimizes their impacts on modeling.
Model Integration and Operation: Integrates ML models into new or existing systems, provides troubleshooting and debugging support, and addresses issues in machine learning infrastructure and workflows.
Tool Development: Develops, maintains, and refines tools, platforms, and services for internal use.
Coding and Documentation: Develops efficient, bug-free code, implements best practices, builds and maintains professional documentation, and tests code for bugs.
Machine Learning Expertise: Maintains familiarity with current developments in the field and integrates knowledge into model development.
Planning & Execution: Manages and coordinates moderately complex tasks, monitors timelines, and provides technical oversight.
Collaboration & Partnership: Collaborates across the organization, supports inclusivity, and aligns on expectations and shared objectives.
Problem Solving: Identifies and addresses moderately complex issues, proactively escalates unresolved issues, and reviews problem-solving strategies.
Continuous Learning: Pursues learning opportunities, seeks feedback, coaches and mentors junior team members, and improves skills.
Performance and Development: Contributes to the talent development pipeline by participating in candidate interviews, assessing candidates, and providing hiring recommendations.
Qualifications
Advanced degree in Computer Science, Statistics, Mathematics, or a related field.
Experience with machine learning frameworks such as TensorFlow, PyTorch, or Keras.
Strong programming skills in Python, R, or another relevant language.
Experience with data preprocessing, feature engineering, and model evaluation.
Knowledge of cloud platforms like AWS, Google Cloud, or Azure.
Experience with data visualization tools such as Matplotlib, Seaborn, or Plotly.
Excellent communication and collaboration skills.
Ability to work independently and manage multiple projects simultaneously.
Skills
Machine Learning
Data Modeling
Software Development
Cloud Platforms
Data Visualization
Collaboration
Problem Solving
Continuous Learning
Benefits
Comprehensive benefits package including medical, dental, vision, short-term and long-term disability, life insurance, AD&D, supplemental life insurance, health care and dependent care FSA, flexible spending accounts, 401(k) savings and investment plan with company match, paid time off, paid sick leave, adoption assistance, employee stock purchase plan, financial planning and group legal, and voluntary benefits.
Pay
$126,200 - $264,100 per year.
Schedule
The role is full-time and permanent.