SecPod is a cybersecurity technology company based in India and the USA. Founded in 2008, SecPod (Security Podium, incarnated as SecPod) builds products and technologies focused on the prevention of cyberattacks. Our flagship platform, SanerNow and SanerCloud, is a state-of-the-art Cyber Hygiene solution that provides continuous, automated, and advanced vulnerability management for IT infrastructure.
We are looking for a skilled AI/ML Engineer to enhance our cybersecurity products with the power of Artificial Intelligence and Machine Learning. The ideal candidate will be responsible for developing and integrating AI/ML models, including classical ML, deep learning, and LLM-based solutions, to strengthen threat detection, risk analysis, and automation capabilities within SecPod products.
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AI/ML Model Development: Design and develop classical ML and deep learning models to predict, detect, and prevent cyber threats. Apply models to real-world cybersecurity datasets.
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ML Fundamentals: Implement supervised, unsupervised, and semi-supervised learning techniques such as regression, classification, clustering, anomaly detection, and ensemble methods.
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LLM Fine-Tuning & RAG Architecture: Fine-tune Large Language Models (LLMs) and build RAG (Retrieval-Augmented Generation) pipelines for tasks such as threat summarization, document understanding, and contextual search.
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Vector Database Integration: Work with vector databases (FAISS, Pinecone, Weaviate, etc.) to build high-performance semantic search solutions.
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Data Analysis & Feature Engineering: Analyze cybersecurity logs, vulnerability reports, and event data to engineer features and extract intelligence using statistical and ML techniques.
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Model Lifecycle Management: Handle the full ML lifecycle from data preprocessing and model training to evaluation, deployment, monitoring, and continuous improvement.
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Model Optimization: Improve model performance with techniques like hyperparameter tuning, cross-validation, transfer learning, and quantization (e.g., QLoRA).
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Collaboration: Work closely with cybersecurity analysts, software engineers, and the R&D team to embed ML and LLM-based solutions into SanerNow’s workflows.
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Research and Innovation: Stay updated with the latest trends in AI, ML, LLMs, cybersecurity, and threat intelligence. Experiment with new tools and techniques to drive innovation.
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Documentation: Prepare detailed technical documentation and present findings and model behaviors to cross-functional teams.
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Bachelor's or Master's degree in computer science, Data Science or a related field.
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Strong understanding of Transformers and core ML concepts and algorithms (e.g., boosting models, decision trees, SVM, KNN, clustering, dimensionality reduction).
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Proficiency in Python and ML libraries/frameworks like Scikit-learn, TensorFlow, PyTorch, Hugging Face Transformers, etc.
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Practical experience in fine-tuning LLMs and working with embedding models (e.g., Sentence-BERT, OpenAI, Cohere).
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Experience building RAG architectures and working with vector databases.
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Knowledge of data preprocessing, EDA, model evaluation metrics, and deployment best practices.
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Familiarity with cybersecurity domain concepts, tools, and real-world threat detection workflows is a strong advantage.
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Experience with MLOps tools (e.g., MLflow, DVC, Docker, FastAPI) is a plus.
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Excellent analytical, problem-solving, and communication skills.
Experience:
0-2 Years (Data Science and AI/ML)]
