Machine Learning Engineer, Differential PrivacyResponsibilities 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.Qualifications 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.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.Company InformationAt 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. 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.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.#J-18808-Ljbffr