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MLOps & Data Infra Developer at Kela Technologies

Tel-Aviv, Tel-Aviv District, Israel -

Full Time

Start Date

Immediate

Expiry Date

06 Jun, 26

Salary

0.0

Posted On

08 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, NumPy, Computer Vision, Deep Learning, 3D Mapping, LiDAR, EO/IR, IMUs, Multi-View Geometry, SLAM, Structure From Motion, Kalman Filters, Probabilistic Modeling

Industry

Software Development

Description

Kela is a defense technology startup pioneering next-generation command-and-control and data infrastructure systems. We empower defense organizations with robust, scalable, and secure platforms that integrate diverse sensors and AI to deliver real-time battlefield intelligence. Backed by leading investors, Kela combines Israeli innovation with global mission impact. Join our Algorithms Department to solve mission-critical, real-world challenges. You will sit at the forefront of national defense, developing cutting-edge technology that bridges the gap between raw sensor data and 3D spatial intelligence. Responsibilities: End-to-End Algorithm R&D- research and implement sophisticated algorithms, spanning the full spectrum from classical Computer Vision to modern Deep Learning. Design systems that achieve high-precision 3D mapping and "reason" across multiple sensor inputs (LiDAR, EO/IR, IMUs) in complex environments. Requirements BSc or MSc in Computer Science, Machine Learning, Data Science, or a related field A natural ability to deconstruct complex, non-standard geometric and mathematical challenges. Strong grasp of Multi-View Geometry, SLAM, or Structure from Motion (SfM) is a major advantage. Professional experience in Python and NumPy for vectorized operations and algorithmic prototyping. Experience with statistical estimation, Kalman filters, or probabilistic modeling is highly valued.

Responsibilities

The role involves end-to-end algorithm research and implementation, spanning Computer Vision to Deep Learning, to design systems for high-precision 3D mapping across diverse sensor inputs.