Member of Technical Staff, Data Research Engineer
$119.8k - $234.7kMicrosoft Corporation
Overview We are seeking Data Research Engineers to join our Multimodal team, where we are building the next generation of foundation models across vision, language, audio, and beyond. If you are passionate about exploring, designing, and building high-quality datasets to drive frontier AI models, this role is for you. At Microsoft AI, data is at the heart of innovation—and in this role, you will collaborate closely with scientists, engineers, and annotators to curate, analyze, and evaluate diverse multimodal data sources critical to model development. You’ll lead efforts in developing novel data collection strategies, improving dataset quality, understanding data-driven model behaviors, and aligning datasets with ethical and societal values. This is a cross‑disciplinary, high‑impact role ideal for engineers who want to push the boundaries of what AI can learn from data, especially in multimodal contexts. Responsibilities Create high-quality datasets for training and evaluation; run experiments on new datasets (data ablations) to assess their impact and determine the most effective data Develop and maintain scalable data pipelines for multimodal ingestion, preprocessing, filtering, and annotation Analyze real‑world multimodal datasets to assess quality, diversity, relevance, and identify areas for improvement Build lightweight tools and workflows for dataset auditing, visualization, and versioning Collaborate with Safety, Ethics, and Governance teams to ensure datasets meet standards for quality, privacy, and responsible AI practices Qualifications Required Qualifications: Bachelor's Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or a related technical field AND 4 years technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR equivalent experience 2 years of experience in data analysis or data engineering Proficiency in statistics and exploratory data analysis methods Ability to communicate technical findings effectively to research and product teams Preferred Qualifications: Master's Degree in Computer Science or related technical field AND 8 years technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR Bachelor's Degree in Computer Science or related technical field AND 12 years technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR equivalent experience. Familiarity with data processing frameworks such as Spark, Ray, Apache Beam Experience working with large-scale, real-world datasets that are unstructured or semi-structured Compensation Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. Certain roles may be eligible for benefits and other compensation. Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 per year. Certain roles may be eligible for benefits and other compensation. Benefits Industry leading healthcare Educational resources Discounts on products and services Savings and investments Maternity and paternity leave Generous time away Giving programs Opportunities to network and connect #J-18808-Ljbffr Microsoft
$139.9k - $274.8k
...benefits. Microsoft AI (MS AI) is seeking a experienced Member of Technical Staff - Data Engineer - Microsoft AI - Copilot to help build mission... ..., infrastructure, application engineers as well as AI Researchers to build next generationdata platformproducts and services...SuggestedOngoing contractWork at officeLocal area- ...models are trained and validated on one of the world’s largest real‑world radiology datasets. About the Role As a Member of Technical Staff in Data Engineering, you will own the systems and workflows that transform Cognita’s raw radiology data into high‑quality datasets...Suggested
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