Here, you will tackle ever-evolving challenges and leverage the dynamic AI landscape to craft solutions that transform the cybersecurity industry. You'll have the chance to build cutting-edge models and AI systems for cybersecurity. You'll gain deep expertise in the fields of both AI and security, engaging with all facets of Generative AI techniques and their deployment in production environments. You will collaborate with a talented team of researchers, engineers and security experts, and play a pivotal role in developing groundbreaking AI solutions. Shape the future of AI for Security with us and make an enduring impact on AI adoption across the world!
Develop and train cutting-edge AI models for the security domain.
Develop a platform for AI data processing, training, fine tuning, evaluation and other AI related needs.
Develop agentic systems that automate and uplift security operations.
Author blog posts, white papers and research papers related to developments in AI for the security landscape.
Collaborate with cross-functional teams of researchers and engineers to translate research ideas into products.
Contribute to our groups culture as an early member of the team.
A PhD in computer science or related fields OR Masters with 2 years of related industry experience OR Bachelors with 4 years of related industry experience.
Strong programming skills in generic programming languages such as Python or Golang.
Experience in one or more of the following areas:
Designing and building scalable, reliable, and secure backend infrastructure (e.g., distributed systems, cloud services, data pipelines, APIs) for large-scale applications.
AI, machine learning, and deep learning technologies, with a solid understanding of core ML concepts such as bias and variance, supervised and unsupervised learning, and Generative AI.
Preferred Qualifications:
Comfortable with fast, iterative development cycles in an environment that requires autonomous thinking, risk taking and bias for action.
Ability to use the latest GenAI technologies and methodologies for software development workflows.
Familiarity with ML frameworks like PyTorch.
Excellent written and verbal communication skills, strong analytical and problem-solving skills.
Fluency in reading academic papers on AI/ML and security and the ability to translate their ideas into prototype or production systems.
