Within AI Platform, the Azure ML team enables data scientists and developers to quickly and easily build, train, deploy, manage, and consume machine learning models. #aiplatform

Responsibilities

As a (Principal) Software Engineer in our team, you will:

• Design & architect core training platform and components to enable large scale workloads of training, fine-tuning on the team

• Work on the architecture, design, and development of the core Training platform powering AzureML to tackle challenging problems in large scale training and fine-tuning of LLMs, LVMs for various tasks such as natural language, text analytics, computer vision, conversational AI, and machine translation using state-of-the-art neural models such as Llama, Falcon, Phi etc

• You will bring knowledge of innovative technologies and collaborate with experts to further it

• As a contributor in a customer-obsessed team, you will collaborate with data scientists and other developers on the team to create the necessary abstractions, infrastructure, interfaces and implement features to train, test, validate for machine learning algorithms including but not limited to data cleaning, model training, hyper parameter tuning at massive, distributed scale. You will also be working on scaling these features for big data using distributed systems. You will drive the incorporation of these customer-inspired innovations into our software. You will take holistic ownership of your features

• Your responsibilities will include architecting, designing, building backend stateful services written in C# hosted on Kubernetes clusters and Docker containers to provide meaningful features to the customers. You will also be designing & implementing Python SDK's existing features, designing new features, implementing them in our distributed, multi-component SDK, and owning the full lifecycle of the features including testing and release

Qualifications

Required Qualification:

• 12+ years of experience writing production code in building internet scale services and distributed systems.

• Ability to debug, read code and work on a large and increasing codebase.

• Engineering knowledge of machine learning systems and data pipelines.

• Experience mentoring other developers, working partners and being a team player.

• Excellent communication and presentation skills

Preferred/Additional Qualifications:

• Preferred demonstrated experience Training, Fine-tuning, Deploying, Inferencing machine learning models at scale.

#IDCAIPlatformHiring

Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations (https://careers.microsoft.com/v2/global/en/accessibility.html) .