Impress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Target Resume Now
About the Role
As our Data Scientist, you will advance our mission to secure Generative AI adoption by building and continuously improving the detection models at the heart of our product. This involves curating high-quality training datasets and tuning production models informed by real-world customer feedback.
Responsibilities
- Build and improve sensitive data detection models end-to-end, defining new sensitive data categories, curating training and evaluation datasets, training and validating models, and shipping production-ready detectors.
- Continuously improve existing models using performance metrics and customer feedback to prioritize retunes and enhance detection accuracy.
- Communicate clearly and proactively in a remote/hybrid team, explaining trade-offs, making recommendations, and collaborating with engineering, security, and product partners.
- Stay current on techniques that improve model and dataset quality.
- Contribute directly to the development of groundbreaking technology for secure Generative AI adoption.
Requirements
- Experience taking classification/NLP models from idea to production and owning them post-launch, including monitoring performance, tuning based on feedback, and improving results.
- Strong applied NLP experience, including transformers, embeddings, and understanding when to use fine-tuning versus simpler classical approaches.
- Experience building and managing high-quality training and evaluation datasets from messy real-world data, including making labeling/taxonomy decisions and demonstrating the impact of dataset quality on model performance.
- Proficiency in running rigorous evaluation and understanding precision/recall trade-offs.
- Expertise in Python and comfort with the modern ML stack (e.g., PyTorch, Hugging Face, scikit-learn).
- Clear communication skills and ability to collaborate effectively within a remote/hybrid team.
- A bias for shipping, demonstrated through pragmatic decisions, fast iteration, and incremental delivery.
Skills
- Classification models
- NLP models
- Transformers
- Embeddings
- Python
- PyTorch
- Hugging Face
- scikit-learn
- Data security
- Sensitive-data classification
- ML system operation in cloud environments (e.g., AWS)
Location
- Remote
- Hybrid
Work Type
- Remote
- Hybrid
- Full-time
Experience Level
- Mid-level
Benefits
- Competitive pay
- Meaningful equity
- Comprehensive benefits
- Pension plan
- Generous PTO
- Flexible hybrid work
About the Company
- Harmonic Security lets teams adopt AI tools safely by protecting sensitive data in real time with minimal effort, giving enterprises full control and stopping leaks so that their teams can innovate confidently.
- Led by cybersecurity experts and backed by top investors including N47, Ten Eleven Ventures, and In-Q-Tel.
- Harmonic exists to help enterprises adopt AI safely and at scale.
- Everyone at Harmonic actively uses AI tools to do their best work, from research and writing to building processes and automating workflows.
- We expect every new hire to bring curiosity about AI and a willingness to use it to work smarter, faster, and more creatively.