Software Engineer 2
3 weeks ago
Overview
At Microsoft, we're passionate about pushing the boundaries of generative artificial intelligence (AI) and natural language understanding. Our Azure Machine Learning Training and Finetuning Team is at the forefront of this mission, working on groundbreaking projects that shape the future of AI-driven applications. We collaborate closely with research institutions, industry leaders, and organizations worldwide to create innovative solutions that impact millions of users.
Qualifications
Required Qualification:
• 5+ 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 Qualification:
Preferred demonstrated experience with training, finetuning, evaluating, deploying large ML models.
#AIPLATFORM
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
As a Software Engineer 2 in our team, you will:
• Work on the 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.
• 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 contributing to and/or backend stateful services written in C# hosted on Kubernetes clusters and Docker containers to provide meaningful features to the customers. You will also be working on improving 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.
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