AI/ML Engineer

We are seeking a dynamic and technically proficient AI/ML Engineer to support our AI/ML R&D initiatives in cybersecurity. The ideal candidate will possess hands-on experience in generative AI, emerging technologies, and product management. This is a hybrid role combining deep technical development with stakeholder engagement.

AI/ML & Cybersecurity Innovation

• Support R&D efforts to prototype generative AI models for real-time threat detection and cybersecurity.
• Design, develop, and deploy machine learning models tailored to cyber threat intelligence and anomaly detection.
• Research and implement novel AI approaches, including multi-agent and reasoning-based systems.
• Develop distributed security monitoring frameworks using tools like AutoGen, CrewAI, etc.
• Build LLM-powered threat analysis tools using LangChain, LlamaIndex, and integrate with enterprise infrastructure.
• Apply MLOps best practices for model deployment, performance monitoring, and continuous integration.
• Optimize vector stores (Qdrant, FAISS, Pinecone, etc.) for RAG-based systems.
• Create synthetic datasets for AI training and model evaluation.
• Use Pydantic for data validation within AI pipelines.
• Conduct technical research, proof of concepts (PoCs) and experimentation on emerging AI/ML use cases.
• Identify opportunities to leverage AI/ML for solving complex problems, including potential applications in cybersecurity and data security.
• Document model architectures, methodologies, experiments, results and technical findings.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or related field.
• 3-5 years of hands-on experience in AI/ML model development and deployment.
• Strong programming expertise in Python.
• Familiarity with LangChain, LlamaIndex, and large language models (LLMs).
• Experience in applying AI to cybersecurity or vulnerability analysis.
• Good understanding of machine learning algorithms, data pipelines, and model evaluation.
• Excellent communication skills for technical and stakeholder engagement.

Preferred Skills

• Exposure to generative AI, LLMs, and chain-of-thought reasoning techniques.
• Working knowledge of MLOps tools such as MLflow, Docker, etc.
• Familiarity with FastAPI or Flask for API development.
• Ability to preprocess, clean, and analyze large datasets efficiently.
• Experience in integrating AI tools with legacy or existing security systems.

Technologies & Frameworks

• LLM Frameworks: LangChain, LlamaIndex
• Multi-agent Systems: AutoGen, CrewAI
• Vector Databases: FAISS, Pinecone, Qdrant, Elasticsearch, AstraDB
• MLOps Tools: MLflow, Docker
• Programming & APIs: Python, FastAPI/Flask
• Data Validation: Pydantic