Microsoft

Principal Software Engineer

Redmond, WA US
USD 133k - 282k
PostgreSQL MySQL C++ C# SQL JavaScript Streaming Kafka AWS Azure Machine Learning Java Python
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Description

Microsoft is a company where passionate innovators come to collaborate, envision what can be and take their careers further. This is a world of more possibilities, more innovation, more openness, and the sky is the limit thinking in a cloud-enabled world.

Microsoft’s Azure Data engineering team is leading the transformation of analytics in the world of data with products like databases, data integration, big data analytics, messaging & real-time analytics, and business intelligence. The products our portfolio include Microsoft Fabric, Azure SQL DB, Azure Cosmos DB, Azure PostgreSQL, Azure MySQL, Azure Synapse Analytics, Azure Service Bus, Azure Event Grid, and Power BI. Our mission is to build the data platform for the age of AI, powering a new class of data-first applications and driving a data culture.

 

We see the opportunity for Azure Database services to leverage the increasingly powerful capabilities of machine learning to automate many of the tasks normally carried out by a database administrator, allowing them to spend their time on challenges unique to their business, while dramatically enhancing database performance and customer experience. The opportunity for autonomy spans all layers of a database service from the virtual machine and operating system configuration to database parameters, and cloud infrastructure layer. The task of building a machine learning model from the ‘data exhaust’ of database service operations requires we that build support for a number of functions, from data acquisition and engineering, data processing, experimentation, followed by deploying a model into production and then actively monitoring performance over time.

 

We are looking for a Principal Software Engineer with experience working with all service aspects of high-throughput and multi-tenant services, able to design components carefully, identify opportunities to reuse existing software and infrastructure, write clean and well-factored code with good tests and maintainability, able to drive architectural changes and influence the roadmap of relevant software components in various database service teams. Your work will directly impact business goals of a wide range of users and facilitate the next wave of growth and innovation in Azure operational databases. You will join a phenomenal team of dedicated engineers and applied scientists with deep experience in database systems, machine learning, data pipelines, and software engineering.  This is a unique opportunity to join a great team and contribute to a strategic initiative with potential to have significant impact for our customers and our database businesses.

 

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. 

 

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

 

We do not just value differences or different perspectives. We seek them out and invite them in so we can tap into the collective power of everyone in the company. As a result, our customers are better served.

Required/Minimum Qualifications

  • Bachelor's Degree in Computer Science, or related technical discipline AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

         o OR equivalent experience.

  • 4+ years of experience in Developing and Running Machine Learning or High Performance Computing (HPC) applications or related exerience

  • 4+ years of experience with Machine Learning software or building associated data pipelines.
  • 2+ years of experience in tuning performance of ML or HPC applications

Other Requirements

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check:

  • This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred/Additional Qualifications

  • Experience with Azure/AWS or other cloud computing platforms is a plus. 
  • Demonstrated experience in working with cloud, big data, machine learning, data science, machine learning operations (MLOps), and distributed systems.
  • Familiarity and/or experience building data pipelines, or real time data streaming technologies and tools like Azure Stream Analytics, Kafka, Flink, and others.

Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $133,600 - $256,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $173,200 - $282,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

 

Microsoft will accept applications for the role until September 20, 2024.

 

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

 

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

 

#azdat #azuredata #MySQL #datascience #datapipelines #machinelearning #mlops

  • Build and deploy data pipeline infrastructure into different database systems to collect training data and store it in the most cost-effective manner possible. Design and implement machine learning model deployment and monitoring.
  • Designs, optimizes, debugs, refactors, and reuses existing code to improve performance and maintainability, effectiveness, and return on investment (ROI).
  • Applies metrics to drive the quality and stability of code, as well as appropriate coding patterns and best practices.
  • Holds accountability and will mentor other engineers across products/solutions, working on call to monitor system/product/service for degradation, downtime, or interruptions.
  • Develops a playbook for the team to resolve issues.
  • Acts as a key contact for leadership to ensure alignment with partners' expectations. Considers partner teams across own organization and their end goals for products to drive and achieve desirable user experiences and fitting dynamic needs of partners/customers through product development.
  • Dedicated to the mission to help ensure Azure Database services are consistent on performance, can scale on-demand, and engineered to withstand the unparalleled computing demand from the customer workloads.
  • Help build a test-driven engineering culture to reduce regressions and bugs in production and will set a higher bar for infrastructure quality.
  • Embody our culture and values
Microsoft
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Data Management Developer Tools DevOps Enterprise Software Operating Systems

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