Senior Machine Learning Engineer

4 hours ago


Bengaluru, India Black Duck Full time

Senior Machine Learning Engineer – AI for AppSec Products Role 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+ Years Mode 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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