Staff Applied Scientist, Generalist

We're hiring applied scientists at multiple levels from Senior to Principal - fully remote within US & Canada!

Who we are

At Gretel, our mission is to build the world’s first developer platform for synthetic data. Our platform solves the data bottleneck problem for developers, data scientists, and AI/ML researchers across multiple modalities including tabular, time-series, relational, language and image. Gretel's APIs automatically fine-tune AI models to generate synthetic data on-demand while protecting privacy and maintaining the utility and accuracy of the original data.

We’re a highly collaborative remote company with employees across the US & Canada. Our innovative and transparent culture offers employees the autonomy, tools, and trust to act like owners and we're looking for a talented Applied Scientist to join our mission!

The impact you’ll have

As an Applied Scientist, you will be working on our core product, coming up with ways to make synthetic data accessible to people everywhere. You'll be researching, shipping and iterating on AI models, including foundational models, and other 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 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 such as Lymphoma without compromising patient identity.

With over 110k developers using Gretel’s platform, millions of models trained, and hundreds of billions of records generated, this is your chance to have a massive impact on the synthetic data industry.

• Partner with product, engineering and applied science to push the boundaries of synthetic data generation and augmentation
• Stay abreast of developments in AI, actively sharing and trying out new approaches
• Mentor colleagues and promote a culture of knowledge sharing
• Be involved in end-to-end development, exploring new applications and techniques within language modeling, generative models for multiple modalities, improving synthetic tabular data generation algorithms, ethical/fair AI, or privacy enhancing technologies.
• Conduct research to improve the performance of large ML and AI models using a diverse collection of datasets and community feedback.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field 
• 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
• 3+ years of industry experience in one or more of the following areas:
  • Deep generative modeling (GANs, transformers, language models, etc.), 
  • Other generative modeling (graphical models, bayesian networks, statistical models)
  • Privacy enhancing technologies (differential privacy, federated learning, etc.), 
  • Classical NLP or computer vision
  • Causal modeling
• Solid Python programming skills and experience with cloud providers such as AWS, GCP, Azure
• Hands-on experience with data wrangling and data manipulation tools and frameworks such as SQL, pandas, or pySpark
• Extensive experience in developing, training, and evaluating ML models, including defining, vetting, and iterating on metrics and running experiments
• A deep understanding of mathematics and statistics in machine learning and/or online controlled experimentation.
• Strong communication skills -– you are able to clearly express ideas both verbally and in written form. We’re a distributed team so we’re extra mindful about communication.

Nice to haves

• Experience creating high-performance implementations of deep learning or machine learning algorithms
• Experience with ML frameworks such as PyTorch, Keras, TensorFlow, HuggingFace, OpenCV, Fairlearn, or MLflow
• Experience with Transformers, LSTM, GANs, CNNs, diffusion models
• Familiarity with information retrieval systems and/or RAG architectures
• Experience with LLM agents
• Experience with differential privacy, hierarchical bayesian models, graphical models, or causal learning
• Experience with online controlled experimentation (A/B testing, interleaving)
• Previous startup experience, especially in SaaS and B2B space
• Advanced degree or other advanced training
• Experience working remotely in a distributed company

At Gretel, we believe that the best ideas come from the blending of diverse perspectives and experiences, which will lead to a stronger company and advancements in technologies. We hire individuals whose peers call them subject matter experts, whose curiosity draws them to new edges of their field and who like to laugh. We are deeply collaborative, apolitical and mission-oriented.

Gretel is an equal opportunity employer. Individuals seeking employment and employees at Gretel are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status, or any other characteristic protected by applicable law.

Compensation

Employee compensation will be determined based on interview performance, level of experience, specialization of skills, and market rate. During the offer discussion, your recruiter will review the finalized base salary, bonus (for applicable roles), benefits and perks (additional information available on our career site), and stock options as they’ll be reflected in the offer letter.