Machine Learning Engineer, Differential Privacy
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 Machine Learning Engineer to join our mission!
The Impact You’ll Have
As a Machine Learning Engineer focused on Differential Privacy (DP), you will play a pivotal role in shaping the future of data privacy.
In this role, your expertise will not only advance the field of differential privacy but also ensure that our products are trusted and ethical. By implementing cutting-edge DP algorithms, you'll be creating safer, more secure data for our users. Your contributions will have a lasting impact on how data privacy is perceived and implemented in the AI/ML industry, setting new standards for responsible innovation.
With over 125k 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.
We are seeking an experienced Machine Learning Engineer with a strong background in implementing DP in AI/ML products. The ideal candidate will be deeply involved in the translation of cutting-edge DP research into practical, scalable solutions, ensuring our products maintain the highest standards of privacy and data security.
Collaborate closely with Applied Scientists to understand the nuances of DP and its applications to generative models.
Design, develop, and implement DP algorithms into our existing and future products.
Optimize the performance of DP techniques in a production environment, balancing privacy guarantees with practical utility and efficiency.
Develop adversarial attacks and privacy auditing mechanisms Conduct rigorous testing and validation of DP models to ensure robustness and reliability.
Stay up to date on the latest developments in DP, machine learning, and data privacy regulations to ensure our products are compliant and industry-leading.
Document and communicate technical findings and recommendations to both technical and non-technical stakeholders.
Master’s or Ph.D. in Computer Science, Mathematics, Engineering, or a related field, with a focus on Differential Privacy, Machine Learning, or a related area.
Proven industry experience in implementing differentially private machine learning algorithms.
Proficient in programming languages such as Python, R, or Java, and familiar with ML frameworks like PyTorch or Tensorflow.
Knowledge of data privacy laws and regulations is a plus.
Excellent problem-solving skills and ability to work in a fast-paced, dynamic environment.
Strong communication skills, with the ability to translate complex technical concepts into easy to understand language.
We think 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.
Accommodations: We celebrate diversity and are committed to creating an inclusive environment for all candidates and employees. If you need assistance or an accommodation due to a disability, please let your recruiter know.
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.Apply for this job