Full-Time ML Architect / Principal Data Scientist

What You'll Do:

• Leading teams of data scientists on full life cycle data-driven solutions.
• Mentoring fellow data scientists and providing guidance on their efforts.
• Data wrangling, preprocessing, and manipulation for ML applications.
• Applying advanced statistical methods and reporting techniques to large datasets.
• Interpreting data analysis and experimental results, and communicating insights.
• Developing ML systems for both supervised and unsupervised learning tasks.
• Mastering DL algorithms and addressing their limitations related to hardware or data.
• Conducting experiments to enhance model performance and clearly reporting outcomes to both technical and non-technical audiences.
• Optimizing DL architectures for performance and supporting systematic optimization efforts.
• Deploying ML solutions across diverse platforms, from large clusters to small SWaP (Size, Weight, and Power) environments.
• Monitoring ongoing model performance to detect and adjust for data drift.
• Following best practices for software documentation and reporting.

Skills You'll Bring:

• Proficiency in ML and DL frameworks, such as scikit-learn, TensorFlow, and PyTorch.
• Excellent leadership skills.
• Excellent written and verbal communication abilities.
• Proficiency in software development, with an emphasis on Python.
• Understanding of validation methods for ML models.
• Experience in distributed version control systems and DevOps tools, such as GitLab, Git, Docker, and Kubernetes.
• Experience with the Linux command line, including bash and shell scripting.
• Expertise in handling large, complex datasets including image, cyber, NLP, and signal data.
• Skills in data preparation and corpus filtering using databases like PostgreSQL and MySQL.
• Familiarity with experimental design for data science projects.
• Competence & experience in full life cycle ML operations (MLOps).