Our team in Azure GenAI is at the cutting edge of developing large language model technologies to power Azure AI Platform products and offering them as a service for both internal and external applications. We collaborate deeply with OpenAI and numerous Microsoft product teams, including GitHub and Office

The team is looking for a passionate, creative, and analytical individual contributor with a background in large language modeling. You will work on adapting and grounding large language models for product-driven scenarios. The focus will be on developing deep learning techniques to enhance the custom copilot experience through efficient adaptation of large-scale language models. The work will span multiple stages of adaptation, including supervised fine-tuning and post-training with Reinforcement Learning from Human Feedback (RLHF)

We are looking for a Senior Machine Learning Engineer to join our team

Microsoft’s mission is to empower every person and every organization on the planet to achieve more, and we’re dedicated to this mission across every aspect of our company. Our culture is centered on embracing a growth mindset and encouraging teams and leaders to bring their best each day. Join us and help shape the future of the world

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

Responsibilities

Responsibilities:

• Development for OpenAI models customization and large scale training 
• Data preparation, training and evaluation of customization tasks 
• Scaling Engineering system and Enterprise readiness 
• Collaboration with product groups in Microsoft 

Qualifications

Required Qualifications :

• Bachelor's Degree in Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) 
• OR Master's Degree in Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) 
• OR Doctorate in Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research) 
• OR equivalent experience

Preferred/Additional Qualifications :

• Rich experience in large language modeling and related areas 
• Understanding of distributed training of LLMs 
• Proven track record of shipping and maintaining cloud services, preferably related to serving machine learning models 
• Publication in top-tier conferences on large language models is a big plus
• Proficiency in programming languages such as Python, and familiarity with machine learning frameworks including PyTorch and Triton
• Experience with data processing and handling large datasets
• Ability to work collaboratively in a team and communicate complex concepts effectively 
  

#IDCAIPHiring

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. 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

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