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Software Engineer

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Microsoft

13d ago

  • Job
    Full-time
    Junior Level
  • Data
    Software Engineering
  • Hyderabad, +1

AI generated summary

  • You need a B Tech/M Tech or equivalent experience, 1+ years in C/C++/Python, knowledge of OSS, Docker, Kubernetes, plus skills in machine learning and enterprise applications.
  • You will engage with partners on LLMs and Diffusion models, optimize GPU performance, manage project risks, collaborate on solutions, and support core AI inference across a large fleet.

Requirements

  • B Tech or M Tech in computer science, engineering, mathematics or a related field, or equivalent industry experience
  • 1+ year(s) of software development experience focused C/C++ and/or Python development
  • Knowledge and experience in OSS, Docker, Kubernetes, Python, GOLANG programming languages
  • Good communication, collaboration skills and a great team player.
  • Experience working in a geo-distributed team
  • Practical experience hosting and running large scale machine learning models in enterprise grade applications.
  • Experience in building enterprise grade applications in C++, Pytho
  • Experience in developing and operating low latency, high scale, reliable online service
  • 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.

Responsibilities

  • Engage directly with key partners to understand state-of-the-art LLMs and Diffusion models, run them at scale in performance and cost effective manner
  • Leverage latest hardware stack technologies improvements in CUDA, infiniband and fast-moving software stack to deliver best of class inference
  • Anticipate, identify, assess, track, and mitigate project risks and issues in a fast-paced start up like environment
  • Motivated to build constructive and effective relationships and solve problems collaboratively
  • Support production inference for core AI scenarios on one of the largest GPU fleets in the world

FAQs

What is the primary focus of the Azure Machine Learning team at Microsoft?

The primary focus is to democratize machine learning and ensure its accessibility to all enterprises, developers, and data scientists, serving billions of requests daily.

What kind of models will I be working with as part of the Inference team?

You will be working with state-of-the-art models including OpenAI models like ChatGPT, as well as models for Bing and Office.

What programming languages should I be proficient in for this role?

You should have experience in C/C++ and/or Python development, along with knowledge of OSS, Docker, Kubernetes, and GOLANG.

What level of experience is required for this position?

A minimum of 1+ years of software development experience is required.

What kind of background is preferred for applicants?

A B Tech or M Tech in computer science, engineering, mathematics, or a related field is preferred, or equivalent industry experience.

Is experience with large-scale machine learning models necessary?

Yes, practical experience hosting and running large-scale machine learning models in enterprise-grade applications is necessary.

Are there any specific security clearance requirements for this position?

Yes, candidates must pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

What kind of team environment should applicants expect?

Applicants can expect a collaborative, innovative team environment that upholds the pursuit of excellence.

Is prior experience working in a geo-distributed team important for this role?

Yes, experience working in a geo-distributed team is preferred.

What responsibilities will I have regarding performance optimization?

You will be tasked with addressing high throughput/low latency scenarios and spearheading performance optimization capabilities.

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