Senior Machine Learning, AI Engineer

🔥 12 hours ago

🇮🇱 Israel – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 12%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Aqua Security

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501 - 1000 employees

🔒 Cybersecurity

Cybersecurity

Aqua Security is the pioneer in securing containerized cloud native applications from development to production. Aqua's full lifecycle solution prevents attacks by enforcing pre-deployment hygiene and mitigates attacks in real time in production, reducing mean time to repair and overall business risk. The Aqua Platform, a Cloud Native Application Protection Platform (CNAPP), integrates security from Code to Cloud, combining the power of agent and agentless technology into a single solution. Founded in 2015, Aqua is headquartered in Boston, MA and Ramat Gan, IL protecting over 500 of the world’s largest enterprises.

📋 Description

• Lead end-to-end development of ML/AI capabilities from problem definition and data preparation through model development, deployment, and continuous improvement • Design and develop proprietary models and algorithms for behavioral analysis, anomaly detection, threat detection, and security risk scoring • Build scalable batch and streaming data pipelines processing security telemetry, runtime events, system logs, and cloud-native activity • Apply statistical methods, classical machine learning, deep learning, and LLMs where they provide measurable value • Drive technical and architectural decisions involving models, frameworks, and infrastructure • Evaluate and optimize model performance, including detection accuracy, precision, recall, false-positive reduction, and inference efficiency • Build and maintain production-grade ML services and APIs with monitoring, observability, model versioning, and automated deployment • Collaborate with security researchers to translate attack techniques and research insights into intelligent detection capabilities • Continuously improve models using real-world data, analyst feedback, and evolving security threats

🎯 Requirements

• 5+ years of hands-on experience developing and deploying AI/ML solutions in production environments • Proven experience building and delivering ML solutions in cybersecurity, threat detection, security analytics, behavioral analytics, or risk analysis • Strong Python programming skills • Experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, or XGBoost • Solid understanding of machine learning fundamentals, statistics, feature engineering, supervised and unsupervised learning, and model evaluation • Experience building data pipelines, working with large datasets, SQL, and production inference systems • Strong Linux skills and practical Bash scripting experience • Understanding of security concepts and system behavior, including processes, networking, identities, containers, and cloud workloads • Proven ability to independently take complex technical challenges from concept to production, with strong engineering ownership • Excellent problem-solving, communication, and collaboration skills • Experience with Go (Golang) is an advantage • Experience with anomaly detection, behavioral analytics, graph-based ML, event correlation, or sequence modeling is an advantage • Experience working with LLMs, embeddings, retrieval, or fine-tuning small language models is an advantage • Familiarity with Kubernetes, cloud environments, distributed systems, or large-scale streaming architectures is an advantage • Background in runtime security, eBPF, attack-path analysis, vulnerability prioritization, or MITRE ATT&CK is an advantage

🏖️ Benefits

• Opportunity to build an AI/ML-driven security product capability from the ground up • Opportunity to shape the technical vision and make core architectural decisions • Ownership of the entire development journey from research and experimentation to scalable, production-ready solutions • Opportunity to influence key technical decisions and shape innovative AI/ML capabilities • Opportunity to work on challenging cloud-native security problems • Full-time employment

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