About the Job
Borneo is a fast-growing startup developing a cutting-edge data security and compliance automation platform, and we're seeking a Staff ML Engineer to join our team and bring new ideas to life by innovating upon our LLM-based solution. This role requires proven experience in LLM and its adaptation to real-world challenges in privacy and security automation. You'll work closely with cross-functional teams to build tools that proactively manage data flows, automate anomaly detection, and streamline compliance processes.
Key Responsibilities
LLM Exploration:
- Drive the development of innovative applications for LLMs in privacy and security, such as multi-model LLM ensembles, advanced privacy risk assessment, and adaptive compliance monitoring.
- Experiment with new architectures and LLM fine-tuning methods, finding unique ways to solve compliance challenges, detect security anomalies, and enforce data privacy rules.
Use Case Expansion: Work collaboratively with Product, Compliance, and Security teams to identify and deliver on high-impact use cases. Potential areas include:
Data Flow Tracking: Building LLM-powered tools that map data movement across systems to preemptively identify privacy risks.
Automated Compliance: Leveraging LLMs to streamline reporting and enforcement of industry-specific regulations.
LLM Optimization:
- Design efficient, scalable LLM models optimized for real-world performance in privacy and security. Regularly refine models to reduce latency, maintain compliance accuracy, and address evolving privacy regulations.
- Integrate LLMs into production environments through CI/CD pipelines, ensuring continuous delivery of new insights, detection capabilities, and compliance improvements.
Leadership:
- Act as a thought leader within the company, exploring the latest advancements in LLM research and how they can be applied to security and privacy.
- Mentor and guide team members, fostering a culture of innovation and best practices in LLM development.
Minimum Qualifications
- 10+ years in software engineering, with at least 5 years working with LLMs, ML or advanced NLP.
- Extensive hands-on experience training, fine-tuning, and optimizing LLMs, such as GPT, BERT or custom models, for applications.
- Proficiency in Python, ML frameworks, and familiarity with cloud environments (AWS, GCP, Azure).
- Strong experience in deploying and maintaining LLM models in production.
- Proficiency in advanced fine-tuning techniques, such as transfer learning, meta-learning, prompt engineering, and using domain-specific datasets for compliance-focused language models.
- Skilled in evaluating models for fairness, interpretability, and explainability, essential for regulatory compliance and ethical AI.
Preferred Experience
- Prior experience working in a startup or early-stage company, where agility and problem-solving are key.
- Experience working in Agile environments with focus on delivering features incrementally.
- Background in privacy-preserving techniques, such as federated learning, differential privacy, homomorphic encryption, and secure multi-party computation.
Why join us
- Impactful Work: Play a key role in developing innovative solutions that help enterprises manage privacy and compliance more effectively.
- Growth Opportunities: Be part of a rapidly growing startup where your contributions will have a direct impact on the company's success.
- Collaborative Environment: Work alongside a talented team of engineers, product managers, and compliance experts who are passionate about what they do.
- Competitive Compensation: We offer a competitive salary and attractive equity options.
