(Senior to Principal) Applied Scientist

$180,000 - $250,000/Yr

Gretel Labs - San Diego, CA

- Senior

San Diego, CA

Publishing Industries

About the position

At Gretel, we're building the platform that developers and data scientists trust for safe, AI-ready data. Our platform combines differential privacy with state-of-the-art AI to generate synthetic data across multiple modalities, whether starting from your own unique data or creating entirely new datasets from prompts. We enable organizations to unlock sensitive data for AI development and analytics. We believe you shouldn't have to search for the right dataset, you should be able to generate exactly what you need while maintaining the highest standards of privacy and utility. As an Applied Scientist, you will be working on our core product with a proactive, builder, customer-focused mindset. You'll identify and build new, better, and safe ways to make synthetic data accessible to people everywhere. You'll be researching, shipping, and iterating on AI models and cutting edge technologies to shape the future of synthetic data, data privacy, and AI ethics. You will unlock real-world use cases with synthetic data generation that our enterprise customers are working on today, including models that can better detect heart disease across genders and ethnicities, financial models that can better respond to unseen data and market changes, and safe datasets that enable medical researchers to share data on rare diseases without compromising patient identity.

Responsibilities

• Explore new applications and techniques within language modeling and generative models for multiple modalities, improving synthetic tabular data generation algorithms, ethical/fair AI, and privacy enhancing technologies.
• Actively collaborate with engineering, sales engineering/solutions architects, product, sales, and marketing as a part of the customer-feedback loop to better understand our end-users and use cases to design and build more effective and efficient solutions.
• Research, design, and build end-to-end reusable, scalable solutions for our customers and users.
• Partner with the sales engineering teams on building complex customer solutions; identify and escalate problems to engineering and support teams.
• Plan, build, and facilitate industry-specific use cases, including content creation in the form of workshops, webinars, technical blogs, whitepapers and developer community engagement.
• Stay abreast of developments in AI, actively sharing and trying out new approaches.
• Mentor colleagues and promote a culture of knowledge sharing.

Requirements

• M.S. or PhD in Computer Science, related technical field, or equivalent practical experience.
• 3+ years of industry experience in building, training, and fine-tuning Machine Learning models, including defining, vetting, and iterating on metrics and running online controlled experiments (A/B testing, interleaving).
• A track record of applied research in AI/ML, as demonstrated by leading research projects, conference presentations, in-depth blog posts, or first author publications.
• Profound experience and understanding across advanced models, such as Transformers, LSTMs, GANs, CNNs, and diffusion models.
• Extensive experience with ML frameworks such as TensorFlow, HuggingFace, PyTorch, Keras, OpenCV, Fairlearn, or MLflow and Python libraries like Pandas.
• Programming experience in Python and experience with Cloud providers such as AWS, GCP, and Azure.
• Builder Mindset - you've contributed to open source projects and/or have built your own model, tool, or product.
• Excellent communication skills - you will interact with customers and/or assist with community-related events, so we're extra mindful about verbal and written communication.

Nice-to-haves

• Experience with privacy enhancing technologies (differential privacy, federated learning, etc.).
• Familiarity with information retrieval systems and/or RAG architectures.
• Experience with LLM agents.
• Previous startup experience, especially in SaaS and B2B space is a plus.
• Experience working remotely in a geographically distributed company.

Benefits

• Employee compensation will be determined based on interview performance, level of experience, specialization of skills, and market rate.
• Salary ranges are updated regularly using premium market data.
• Senior Applied Scientist $180,000-$210,000 USD
• Staff Applied Scientist $200,000-$230,000 USD
• Principal Applied Scientist $220,000-$250,000 USD