Title: Machine Learning Engineer (Full-Time / Equity Option)
Location: Remote
Company: Absentia Technologies
Industry: Artificial Intelligence
- Defense
- Aerospace
- Autonomy
About Us
Absentia Technologies is an AI research and defense technology company creating modular, mission-adaptable agents for perception, prediction, and autonomy. From satellites and drones to battlefield awareness and scientific applications, our systems power decision-making where clarity is critical.
We develop focused agents that can work independently or in collaboration:
Ghost – Restores visibility through smoke, fog, haze, turbidity, and other obstructions
Specter – Enhances low-light and obscured visuals across EO/IR/LiDAR/radar
Phantom – Enables object detection, anomaly identification, and imagery intelligence
Wraith – Simulates future states and forecasts spatial/temporal battlefield conditions
Spirit – Corrects distortion from atmospheric interference to restore spatial clarity
Shade – Removes light pollution and urban skyglow from nighttime imagery
Our early agents — Ghost, Specter, and Phantom — are entering beta. We’ve applied for over a dozen government grants and are working toward pilot deployments in both commercial and defense sectors. With hardware on the roadmap and real-time demos in progress, now is the time to join our core engineering team.
The Role
We're looking for a Machine Learning Engineer who thrives in high-uncertainty, high-autonomy environments. You’ll help us develop, train, and deploy deep learning models for image-based perception, real-time simulation, and autonomous agent behavior. You’ll work directly with the CEO and founding team to scale our tech into real-world systems.
Responsibilities
Design and train computer vision models for satellite, aerial, and underwater imagery
Build and maintain scalable ML pipelines for model training and inference
Prototype and refine core models for edge deployments (drones, small systems, etc.)
Collaborate on tools for prediction, anomaly detection, and battlefield simulation
Contribute to research, experimentation, and integration of ML across modular agents
Requirements
Strong experience with PyTorch or TensorFlow
Proficiency in computer vision, deep learning, and model optimization
Solid understanding of CNNs, transformers, and real-time inference techniques
Experience with data annotation, augmentation, and evaluation metrics
Bonus: experience with autonomous systems, geospatial data, or defense applications
What We Offer
Competitive equity in a high-growth dual-use startup
Remote-first, flexible work environment
Direct impact on national security, autonomy, and AI research
Opportunity to shape the technical direction of an early-stage company
Future Full-time Compensation (post-funding) And Benefits For Early Contributors
Ideal Candidate
You’re comfortable in ambiguity, driven by mission, and excited to see your models in the real world. You’re looking to build something meaningful — not just optimize ads.
