Senior AI/ML Engineer with Network Security

Get to know us better

CodiLime is a software and network engineering industry expert and the first-choice service partner for top global networking hardware providers, software providers and telecoms. We create proofs-of-concept, help our clients build new products, nurture existing ones and provide services in production environments. Our clients include both tech startups and big players in various industries and geographic locations (US, Japan, Israel, Europe).

While no longer a startup - we have 250+ people on board and have been operating since 2011 we’ve kept our people-oriented culture. Our values are simple:

• Act to deliver.
• Disrupt to grow.
• Team up to win.

The project and the team

We develop software for modern platforms and operating systems for leading networking equipment manufacturers, as well as various other cloud-native, containerized services and solutions.

We are looking for an AI/ML engineer with network security experience to validate, train, and develop AI models for security threat detection.

What else you should know:

• The client is based in the US, with some employees located in India
• Close cooperation with the client’s representatives will be required
• The client’s AI/ML experts are already working on the project
• Online meetings in US-friendly hours (6:00PM, 7:00PM) will be required two to three times a week

Your role

As a part of the team, will be responsible for:

• Developing an innovative cybersecurity product that leverages cutting-edge analytics, machine learning, and threat intelligence to provide advanced threat detection and incident response capabilities
• Preprocessing network data, extracting features, and building ML/DL models and pipelines for threat detection
• Evaluating the effectiveness of ML/DL models, proposing and implementing changes to reduce false positives
• Developing scripts for continuous ML/DL monitoring and retraining/redeployment triggers
• Optimizing ML/DL models to ensure appropriate inference performance
• Explaining how ML/DL models operate and why specific threats are flagged, ensuring transparency and understandability of model decisions
• Participating in technical discussions with the team and the client

Do we have a match

As a Senior AI/ML Engineer, you must meet most of the following criteria:

• Strong understanding of fundamental ML concepts (supervised/unsupervised learning, regularization, etc.). Hands-on experience with various classic ML models (classification, regression, clustering, anomaly detection) and with DL models using various neural network architectures (CNNs, RNNs, LSTMs, Transformers, etc.)
• Deep experience with PyTorch for model development, training, evaluation, and deployment. Ability to write custom layers, loss functions, and use the PyTorch ecosystem
• Experience with network security, including in-depth knowledge of TCP/IP, DNS, HTTP, and TLS protocols, as well as analyzing flow and PCAP data for threat detection
• Advanced Python programming skills for AI/ML model development and network security analysis, including experience with core and specialized libraries for efficient data processing, feature engineering, and scalable model deployment (PyTorch, Scikit-learn, Pandas/NumPy, Scapy, etc.)
• Familiarity with containerization and cloud deployment (AWS preferred)
• Ability to work both independently and in a team
• English at least B2 level, C1/C2 preferred

A perfect match candidate will also possess the following experience:

• Experience in evaluating and monitoring AI models: imbalanced classification know‑how, live metrics for drift/skew/quality, alert volume controls, creating automated retraining/redeployment triggers
• Experience with behavioral modeling using network data: applying ML techniques to analyze and model behaviors in networked or graph-structured data, ability to extract features, detect patterns, and infer relationships or anomalies within large-scale, complex networks
• Ability to use threat intelligence and ML/DL techniques to analyze network traffic, detect malware operations, and identify suspicious activities such as connections to malware servers
• Experience with Explainable AI (XAI): knowledge of XAI techniques and tools (e.g., SHAP, LIME, Captum) for interpreting and explaining AI models predictions
• Proven ability to design and implement anomaly detection models using unsupervised learning techniques, such as clustering, autoencoders, and dimensionality reduction, to identify unusual patterns or outliers in large-scale datasets, crucial for detecting unknown threats or emerging malware behaviors

More reasons to join us

• Flexible working hours and approach to work: fully remotely, in the office or hybrid
• Professional growth supported by internal training sessions and a training budget
• Solid onboarding with a hands-on approach to give you an easy start
• A great atmosphere among professionals who are passionate about their work
• The ability to change the project you work on