Senior Algorithm Engineer

2 weeks ago

Petah Tikva, Central District, Israel mprest Full time

We are looking for a Senior Algorithm Engineer to join a high-velocity R&D team developing advanced real-time algorithms for mission-critical defense systems.

The role focuses on designing, implementing, and evolving estimation, inference, and decision algorithms that operate under real-world constraints such as uncertainty, latency, partial observability, and adversarial conditions. You will take ownership of core algorithmic components from theoretical formulation through deployment in operational systems.

Requirements:

  • MSc or PhD in Electrical Engineering, Aerospace Engineering, Computer Science, Applied Mathematics, or Physics.
  • Strong theoretical and practical background in probabilistic estimation, Bayesian inference, and stochastic systems.
  • Proven experience developing real-time algorithms for complex, sensor-driven systems (defense, aerospace, robotics, automotive, or similar domains).
  • Excellent foundation in linear algebra, probability theory, estimation methods, and numerical computation.
  • Hands-on experience implementing production-grade algorithms in Python or similar.
  • Experience dealing with asynchronous inputs, missing or degraded data, and noisy measurements.
  • Ability to reason rigorously about algorithm behavior under non-ideal and adversarial conditions.
  • Comfortable operating in a fast-paced, high-ownership environment with minimal supervision.

Advantages

  • Experience with defense or security command-and-control systems.
  • Familiarity with advanced estimation, hypothesis management, or density-based modeling techniques.
  • Background in hybrid model-based and learning-based algorithmic approaches.
  • Publications, patents, or demonstrable academically rigorous work.
  • Valid Level 3 Security Clearance or eligibility.

Responsibilities:

  • Design, implement, and maintain real-time estimation and inference algorithms operating on heterogeneous sensor inputs.
  • Develop and tune probabilistic state-estimation models, including non-linear filters, adaptive models, and prediction mechanisms.
  • Implement uncertainty management, gating, clustering, hypothesis handling, and state lifecycle logic.
  • Integrate AI/ML components where they provide measurable value (classification, anomaly detection, decision support).
  • Own algorithm performance across stability, convergence, latency, and numerical robustness metrics.
  • Translate operational and system-level needs into mathematical formulations and deployable algorithms.
  • Collaborate closely with system engineers and software teams to integrate algorithms into real-time command-and-control environments.
  • Analyze operational data, simulations, and edge cases; iteratively refine models based on empirical performance.
  • Participate in algorithm design reviews, trade-off analyses, and performance assessments.

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