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As an Applied Engineer II you will play a pivotal role in contributing to the development and integration of cutting-edge AI technologies into Microsoft products and services and ensuring they are inclusive, ethical, and impactful. You will collaborate across product, research, and engineering teams to bring innovative solutions to life, applying your experience in machine learning, data science, and AI. Your work will directly influence product direction and customer experiences.
Job Responsibility:
Research and implement state-of-the-art technologies using foundation models, prompt engineering, Retrieval Augmented Generation (RAG), graphs, multi-agent architectures, as well as classical machine learning techniques
Fine-tune foundation models using domain-specific datasets
Evaluate model behavior on relevance, bias, hallucination, and response quality via offline evaluations, shadow experiments, and online experiments
Build rapid AI solution prototypes, contribute to production deployment of these solutions, debug production code, and support Machine Learning and AI operations
Utilize experience in AI subfields (e.g., deep learning, Generative AI, Natural Language Processing (NLP), muti-modal models) to translate cutting-edge research into practical, real-world solutions that drive product innovation and business impact
Apply an understanding of fairness and bias in AI by proactively identifying and mitigating ethical and security risks—including XPIA (Cross-Prompt Injection Attack) unfairness, bias, and privacy concerns—to ensure equitable and responsible outcomes
Requirements:
Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
OR equivalent experience
Ability to meet Microsoft, customer and/or government security screening requirements
Microsoft Cloud Background Check upon hire/transfer and every two years thereafter
Nice to have:
1+ year of experience with Generative AI OR Large Language Models/Machine Learning algorithms (e.g., LangChain, PromptFlow) and experience with Machine Learning Operations Workflows, including Continuous Integration/Continuous Delivery (CI/CD), monitoring, and retraining pipelines
1+ year of experience developing and deploying live production systems
2+ experience across the product lifecycle from ideation to shipping