Radar AI / ML Algorithms Engineer

At Algolight, we live and breathe the future of artificial intelligence and the physical world.

🌍 Learn more about us: https://algolightltd.com

Our mission it two-folder:

On the civilian side, we build labeled 3D information layers and foundation models from all types of sensors—for smart cities, drones, autonomous vehicles, infrastructure, public safety, and far beyond.

On the defense side, we bring true real-time intelligence to the edge—anywhere, for any sensor, at any point on the map—enabling smart, real-time decisions in the field.

Border Team Mission

At Algolight, we are building the next generation of autonomous, multi-sensor AI systems designed to operate in real, operational environments — not just in theory. Our work spans from raw sensor data to high-confidence triage, reasoning, and autonomous decision-making, enabling scalable, robust, and intelligent systems that reduce cognitive load on operators and help drive safer, more effective national operations.

As part of a national effort to modernize border operations, you will be a core technical force — helping define, design, implement, and scale AI-driven architectures that tie together data, models, agents, and operational systems.

🚀 What You’ll Be Responsible For

AI-Driven Radar Understanding

• Develop machine learning and deep learning models that operate directly on raw or minimally processed radar data.
• Treat radar signals as spatiotemporal data, enabling:
• Detection, classification, and behavior inference
• Scene understanding and anomaly detection
• Replace or augment classical pipelines with learned or hybrid AI-based approaches.
• Design data-driven detection and tracking systems

Multi-Sensor Fusion (AI-Centric)

• Integrate radar into multi-modal learning systems:Radar + vision (EO/IR), event cameras, acoustic, etc
• Develop Cross-modal representations and Learned fusion strategies instead of rule-based fusion
• Support downstream AI modules such as: Event triage, scoring, reasoning, and autonomous decision systems

Research to Production (ML Systems)

• Translate ML research into real-time, production-grade systems
• Train, evaluate, and benchmark models on real-world datasets

🎯 What We Are Looking For

Required Qualifications

• Strong background in machine learning / deep learning applied to physical or sensor data
• experience in algorithm development (ML / AI / signal-based domains)
• Ability to work directly with raw, noisy, real-world data
• Strong programming skills

Technical Strengths (ML-Oriented)

• Deep learning (CNNs, Transformers, sequence models)
• Representation learning and self-supervised learning
• Time-series and spatiotemporal modeling
• Handling uncertain, incomplete, and adversarial data
• Model validation, benchmarking, and iteration in real-world conditions

⭐ Strong Advantages

• Experience combining classical radar/signal processing with ML approaches
• Work on multi-modal perception systems
• Experience with real-time or edge ML deployment
• Background in taking models from research → production
• Experience with radar systems (defense, automotive, or sensing domains)

🌟 What Awaits You at Algolight

• Ownership over AI-driven radar intelligence at national scale
• Real sensor data, real environments, real constraints
• Freedom to move beyond classical pipelines into learning-based systems
• Collaboration with top-tier AI, perception, and sensing experts
• A culture that values depth, rigor, and real-world performance over buzzwords

🔎 Sensors We Work With

UV, VIS, NIR, SWIR, MWIR, LWIR, Bolometric, Radar, Microphone, Geophone, SAR, Polarimetric cameras, Fiber sensing, Event cameras, Multi-/Hyper-spectral, Laser imaging cameras, Vibrometers, and more.