Microsoft
Software Engineer - AI/ML, Multiple Locations
Microsoft, Redmond, Washington, United States, 98052
Software Engineer - AI/ML, Multiple Locations
Overview: Come build community, explore your passions, and do your best work at Microsoft. This opportunity will allow you to bring your aspirations, talent, potential - and excitement for the journey ahead. We're a company of learn-it-alls rather than know-it-alls, and our culture is centered around embracing a growth mindset, inspiring excellence, and encouraging teams and leaders to bring their best each day. As a Software Engineer on AI and/or ML projects, you will develop software, tools, and code to be used in support of design, infrastructure, and technology platforms including large and small language models (LLMs/SLMs). You will create and implement extensible and maintainable code and prompts for a product, service, or feature. You will partner with stakeholders to determine user requirements for a feature and incorporate insights into future designs or solution fixes. You will collaborate with others to create a clear plan for testing, assuring quality of solutions while applying knowledge of debugging tools, logs, telemetry, and other methods to proactively flag issues. You will also learn about customer scaling requirements and the application of best practices for meeting scaling needs and performance expectations, while ensuring security, privacy, safety, and accessibility. You will consider the impact of AI technology, including applying Microsoft's responsible AI practices. Responsibilities: Learn to review and break down work items into tasks with stakeholder collaboration, provide estimations, and escalate delays while supporting feature deployments to customers. Collaborate with key stakeholders to define feature requirements, integrate feedback to enhance design, and establish feedback loops for continuous improvement based on customer metrics. Evaluate AI technologies (such as LLMs, SLMs, embeddings) and architectures (such as orchestration patterns, RAG, etc.) when developing solutions. Specify or implement AI platform improvements like fine-tuning or training custom ML models. Learn and apply coding standards and best practices through code reviews, developing maintainable and extensible code with guidance. Utilize debugging tools to proactively and reactively address issues in product features, ensuring code quality and reliability. Support the identification of dependencies and design documentation for product features, learn about system interactions and back-end dependencies, and contribute to architectural processes under guidance. Produce code to test hypotheses for technical solutions and assist with technical validation efforts. Collaborate on quality assurance plans, augment test cases, and integrate automation into testing, while understanding security and compliance implications in system architecture. Contribute to data analysis and feedback integration for product engineering decisions, acting as a Designated Responsible Individual (DRI) for monitoring and restoring system functionality within Service Level Agreement (SLA) timeframe. Participate in live service operations, and support telemetry data integration for system behavior insights, focusing on performance, reliability, and safety. Develop and apply best practices for reliable code building, understand global and local regulations, customer scaling requirements, and support communication with key partners across Microsoft for user experience enhancement and partner needs. Ensure compliance with security, privacy, safety, and accessibility standards, leverage developer tools for code creation and debugging, contribute to automation in production and deployment, and proactively seek knowledge to improve product availability, reliability, efficiency, and performance at scale. Understand and apply Microsoft's responsible AI practices to ensure systems meet our commitments to our customers. Helping diverse candidates find great careers is our goal. The information you provide here is secure and confidential.
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Overview: Come build community, explore your passions, and do your best work at Microsoft. This opportunity will allow you to bring your aspirations, talent, potential - and excitement for the journey ahead. We're a company of learn-it-alls rather than know-it-alls, and our culture is centered around embracing a growth mindset, inspiring excellence, and encouraging teams and leaders to bring their best each day. As a Software Engineer on AI and/or ML projects, you will develop software, tools, and code to be used in support of design, infrastructure, and technology platforms including large and small language models (LLMs/SLMs). You will create and implement extensible and maintainable code and prompts for a product, service, or feature. You will partner with stakeholders to determine user requirements for a feature and incorporate insights into future designs or solution fixes. You will collaborate with others to create a clear plan for testing, assuring quality of solutions while applying knowledge of debugging tools, logs, telemetry, and other methods to proactively flag issues. You will also learn about customer scaling requirements and the application of best practices for meeting scaling needs and performance expectations, while ensuring security, privacy, safety, and accessibility. You will consider the impact of AI technology, including applying Microsoft's responsible AI practices. Responsibilities: Learn to review and break down work items into tasks with stakeholder collaboration, provide estimations, and escalate delays while supporting feature deployments to customers. Collaborate with key stakeholders to define feature requirements, integrate feedback to enhance design, and establish feedback loops for continuous improvement based on customer metrics. Evaluate AI technologies (such as LLMs, SLMs, embeddings) and architectures (such as orchestration patterns, RAG, etc.) when developing solutions. Specify or implement AI platform improvements like fine-tuning or training custom ML models. Learn and apply coding standards and best practices through code reviews, developing maintainable and extensible code with guidance. Utilize debugging tools to proactively and reactively address issues in product features, ensuring code quality and reliability. Support the identification of dependencies and design documentation for product features, learn about system interactions and back-end dependencies, and contribute to architectural processes under guidance. Produce code to test hypotheses for technical solutions and assist with technical validation efforts. Collaborate on quality assurance plans, augment test cases, and integrate automation into testing, while understanding security and compliance implications in system architecture. Contribute to data analysis and feedback integration for product engineering decisions, acting as a Designated Responsible Individual (DRI) for monitoring and restoring system functionality within Service Level Agreement (SLA) timeframe. Participate in live service operations, and support telemetry data integration for system behavior insights, focusing on performance, reliability, and safety. Develop and apply best practices for reliable code building, understand global and local regulations, customer scaling requirements, and support communication with key partners across Microsoft for user experience enhancement and partner needs. Ensure compliance with security, privacy, safety, and accessibility standards, leverage developer tools for code creation and debugging, contribute to automation in production and deployment, and proactively seek knowledge to improve product availability, reliability, efficiency, and performance at scale. Understand and apply Microsoft's responsible AI practices to ensure systems meet our commitments to our customers. Helping diverse candidates find great careers is our goal. The information you provide here is secure and confidential.
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