AI/ML Specialist with Cybersecurity - Lead

We are looking for an AI/ML Engineer (Cyber Security & Networking) who can design and develop advanced machine learning models to drive innovation in network security and product optimization. This role requires a self-starter with strong problem-solving skills, a passion for tackling technical challenges, and the ability to deliver impactful results in a fast-paced start-up environment. You will work closely with cross-functional teams and stakeholders to build scalable AI-driven solutions that enhance security, improve product performance, and optimize business outcomes.

• Develop and deploy ML models for threat intelligence, anomaly detection, and cyber security applications
  

• Collaborate with product managers and stakeholders to define project objectives and measurable outcomes

• Architect and implement AI solutions to improve network management and product efficiency
  

• Lead the design of algorithms, data pipelines, and predictive models to optimize customer experiences and revenue

• Monitor, analyze, and improve model performance to ensure scalability, reliability, and accuracy

• Coordinate with engineering and data science teams for seamless integration of AI solutions into products

• Effectively communicate progress, challenges, and solutions to senior management and stakeholders

  
  
  

• Bachelor's degree in Engineering/Computer Science with 45 years of experience in AI/ML applications

• Proven experience in developing ML models for cyber security and networking domains
  

• Strong knowledge of clustering, decision trees, neural networks, and anomaly detection techniques
  

• Proficiency in TensorFlow, PyTorch, Keras, and Natural Language Processing (NLP)
  

• Solid foundation in statistical techniques (regression, distributions, hypothesis testing, etc.)

• Excellent analytical, problem-solving, and communication skills
  

• Ability to work independently in a start-up, growth-driven environment
  

  
  

• Experience in deploying ML models at scale in cloud environments (AWS, GCP, Azure)
  

• Exposure to cyber threat intelligence platforms and network monitoring tools

• Contributions to open-source AI/ML projects
  

• Familiarity with DevOps/MLOps practices for AI model lifecycle management