Virtualitics is trailblazing Intelligent Exploration and Enterprise AI with our cutting-edge AI Platform. We are hiring an ML Applications Engineer with the capability and readiness to obtain a U.S.-government security clearance. This role is pivotal in bridging the worlds of machine learning, data engineering, and software development to enhance our AI data applications. Career advancement opportunities are available for those interested in senior engineering positions and technical leadership.
As an ML Applications Engineer, you will:
Design, develop, and maintain scalable software solutions built using the Virtualitics SDK to process and analyze large datasets.
Architect and implement data pipelines and workflows to ensure efficient data collection, processing, and storage.
Optimize data access patterns, enhancing the efficiency and performance of our AI solutions.
Assess and address runtime performance issues, ensuring high responsiveness and stability of applications.
Write clean, efficient, and maintainable code following best practices in software development.
Collaborate closely with Technical Product Managers to implement usability enhancements in our applications, ensuring our products meet and exceed user expectations.
Architect robust, scalable, and user-friendly applications, considering current trends and future growth.
Craft and manage dynamic dashboards using the Virtualitics AI Platform Python SDK, transforming data into intuitive visuals for decision-making.
Stay updated with the latest advancements in software engineering and data science fields and apply them to improve existing solutions.
Requirements:
A degree in Computer Science or related field, or 4+ years of software engineering experience.
Must be open to obtaining and maintaining a U.S. government security clearance.
Proficiency in Python with a solid understanding of Python Data Stack (pandas, NumPy, scikit-learn, PyTorch, Matplotlib, etc.).
Proven track record of deploying software into production environments.
Familiarity with Docker, Kubernetes, and Git.
Exceptional problem-solving skills and a keen sense of ownership.
Excellent communication skills in English, both written and verbal.
Pluses:
Experience in Machine Learning Engineering roles and the end-to-end lifecycle of AI applications, from model development to deployment.
1+ years of experience with technologies like task schedulers (e.g. Celery, Airflow, Prefect, etc.) and web-app development stacks (e.g. Flask/Django) or app building kits like Streamlit/Plotly Dash.
Experience with Predictive Maintenance, USAF Data Sources, Supply Chain, Scheduling Optimization, etc.
US DOD Security Clearance (Secret or TS/SCI)
Experience with Cyber Analytics, PCAP and network monitoring, CVEs and Cyber Vulnerabilities, etc.
Compensation and Benefits:
Competitive salary/equity/bonus based on experience and education.
Comprehensive benefits package including medical, dental, and vision.