Job Description

Description

Title: Machine Learning Engineer

Job Description:
We are seeking a skilled ML Engineer to design, build, and deploy advanced ML solutions that drive analytics, anomaly detection, and data classification across enterprise-scale environments.

This role will focus on developing and optimizing models, including LLMs and prompt engineering pipelines, and ensuring seamless integration into production workflows spanning cloud-native, on-premises, and Databricks ecosystems.

The ideal candidate combines hands-on ML engineering expertise with strong programming skills, MLOps best practices, and experience with big data platforms. You will collaborate closely with data scientists, software engineers, and cybersecurity researchers to transform research into production-grade solutions that enhance data-driven insights and threat detection capabilities. This position is an exciting opportunity for someone eager to push the boundaries of applied ML, working with LLMs, embeddings, vector databases, RAG frameworks, and distributed systems to deliver high-performance, cost-efficient models.

 

Key Responsibilities  

• Design, build, and deploy ML models for user behavior analytics, anomaly detection, and data classification across enterprise environments.  
• Collaborate with data scientists, software and data engineers to integrate ML models into production pipelines, cloud-native environments, on-premises, and Databricks workflows.  
• Develop, fine-tune, and evaluate LLMs and prompt engineering solutions for data classification, labeling, and threat analysis features.
• Optimize models using techniques like distillation, quantization, and efficient data structures to boost performance and lower resource cost.
• Build high-performance data inputs using embeddings, vector databases, and distributed training frameworks.
• Manage model lifecycle and performance via MLOps best practices: monitoring, retraining, and deploying updates.
• Partner with data scientists, cybersecurity researchers and product teams to evaluate and refine ML-driven capabilities.
• Conduct experiments and benchmark results in fast-paced, data-intensive environments.

 

Requirements

• Bachelor’s degree in computer science, data science, or related field.
• 3+ years of experience in Machine Learning engineering or ML-adjacent roles (data science, MLOps, AI).
• Strong programming proficiency in Python , familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Hands-on experience with LLMs, prompt engineering, vector embedding techniques, or related technologies.
• Proficiency with big data platforms like Databricks , PySpark , and cloud services (Azure, AWS)
• Experience with MLOps tools and deployment (CI/CD, containerization, Kubernetes, etc.).
• Experience with vector DBs, retrieval-augmented generation (RAG) frameworks like Langchain
• Solid analytical and debugging skills with ability to translate research insights into production code.
• Nice-to-have:
• Prior experience working on cybersecurity or data protection products
• Familiarity with user behavior-based threat detection, anomaly detection, or metadata analytics
• Statistical modeling and prompt evaluation ability (e.g., response coherency, relevance).

 

 

We invite you to check out our Instagram Page to gain further insight into the Varonis culture!  

@VaronisLife  

Varonis is an equal-opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, national origin, disability, veteran status, and other legally protected characteristics

 

Job Tags

Full time,

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