Senior Machine Learning Engineer

1 week ago

New Delhi, India Black Duck Full time

Senior Machine Learning Engineer – AI for AppSec ProductsRole Summary:As a Senior Product-focused Machine Learning Engineer, Research, design, development, and deployment of advanced LLM-powered systems that secure enterprise software development lifecycles. Work bridges cutting-edge AI research and scalable product delivery, driving innovation in AppSec / cybersecurity tooling used across large-scale production environments.your work bridges foundational AI research and product deployment, with close collaboration alongside engineering and product teams.You will Research, Build LLM-integrated systems for vulnerability detection, open source risk analysis, and secure software supply chain intelligence. Driving end-to-end development of models and infrastructure deployed in CI/CD pipelines.You have led the development of patented copilots, vulnerability fuzzers, and intelligent code analyzers built on LLMs, now integrated into secure SDLC pipelines and used across large-scale production environments.Job Location : Black Duck, Bangalore (Opp Christ University, Near Diary Circle)Experience Level : 5+ YearsMode of work : Hybrid (3 Days WFO)Key Responsibilities:- Research, Architect, Design and scale LLM-based copilots, vulnerability fuzzers, and intelligent code analyzers for secure SDLC integration. - Involved in end-to-end development of patented AI systems, from prototyping to production deployment. - Collaborate cross-functionally with cross geo engineering, product, and security teams to align AI capabilities with strategic goals. - Translate foundational research into robust, enterprise-ready solutions with measurable impact. - Take initiatives across AI and cybersecurity. - Ensure compliance with secure coding, model governance, and responsible AI practices.Technologies & Tools:- Programming: Python (must), plus experience with C/C++ or Rust for low-level security tools. - ML/AI Tools: PyTorch, TensorFlow, Scikit-learn, Open AI, Hugging Face. - Security Tools: Experience with fuzzers (e.g., AFL, lib Fuzzer), SAST/DAST tools, or custom analyzers. - Cloud & DevOps: AWS/GCP/Azure, Docker, Kubernetes, GitHub Actions.Impact Highlights:- Delivered LLM-powered copilots adopted across multiple enterprise environments, improving developer productivity and code security. - Developed intelligent fuzzers and analyzers that proactively detect vulnerabilities, reducing triage and remediation time. - Contributed to patented AI systems now embedded in production pipelines, enhancing resilience and compliance.

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