Machine Learning Engineer

Virtualitics is the category leader in AI-native readiness applications for defense, government, and critical infrastructure. Founded on a decade of Caltech research in partnership with NASA/JPL, we are led by scientists, strategists, and servicemembers united by a single mission: to solve the world’s most complex, mission-critical challenges with AI. 

Our Readiness AI solutions deliver operational certainty — giving leaders and operators a clear picture of what’s ready, what’s at risk, and what to do next. By identifying risks early, diagnosing root causes, and recommending prioritized actions with transparent, explainable AI, we help organizations move from data complexity to decision advantage. 

Behind that impact is relentless innovation. Inventors at heart, we hold 15+ U.S. patents and are leading the shift toward agent-driven readiness. But what truly sets us apart is our culture — relentless about results, grounded in transparency, and driven by compassion for the mission and the people it serves.

If you’re motivated by impact, inspired by technical depth, and ready to build AI that performs where it matters most — you’ll find your mission here.

As an ML Applications Engineer, you will:

• Spearhead platform upgrades, ensuring our products are at the forefront of innovation and effectiveness.

• Craft and manage dynamic dashboards using the Virtualitics AI Platform Python SDK, transforming data into intuitive visuals for decision-making.

• Optimize data access patterns, enhancing the efficiency and performance of our AI solutions.

• Tackle runtime performance issues, ensuring high responsiveness and stability of applications.

• Architect robust, scalable, and user-friendly applications, considering current trends and future growth.

• Collaborate closely with Technical Product Managers to drive usability enhancements, ensuring our products meet and exceed user expectations.

Requirements:

• A degree in Computer Science or related field, or 4+ years of software engineering experience.

• Must have a TS/SCI security clearance.

• Must be willing to travel and work from a SCIF as needed.

• Proven track record of deploying software into production environments.

• Proficiency in Python with a solid understanding of Python Data Stack (pandas, NumPy, scikit-learn, PyTorch, Matplotlib, etc.).

• Experience with big data technologies and frameworks (Spark, Databricks, Snowflake, etc).

• 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.

• Experience with Predictive Maintenance, Supply Chain, Scheduling Optimization, etc.

• Experience with PCAP and network monitoring, CVEs and Cyber Vulnerabilities, etc. 

• 1 year 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.

Compensation and Benefits:

• Competitive salary/equity/bonus based on experience and education.

• Comprehensive benefits package including medical, dental, and vision.

• Unlimited paid time off.