Senior Machine Learning Engineer

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.

The AI Platform organization at Microsoft builds the end-to-end Azure AI stack/PaaS and is core to Azure’s innovation and differentiation, as well as all of Microsoft’s flagship products, from Office to Teams, to Xbox. We are the team building Azure OpenAI, Azure ML, Cognitive Services, and the global Azure AI infrastructure for running the largest AI workloads on the planet. 

Within the AI Platform, our Evaluation AI team specializes in building evaluation frameworks for cutting-edge deep learning models, including Large Language Models, Small Language Models, RAG, fine-tuned, and distilled models across NLP, vision, multimodal, Co-pilot and agentic frameworks. We build the next-generation model evaluation platform for generative applications, leveraging state-of-the-art (SOTA) OSS and OAI models.

We are looking for a passionate, creative, analytical Machine Learning Engineer who loves NLP, deep learning and wants to ship products quickly at a massive scale. We will provide a lot of opportunities for you to learn, grow and contribute.

Required Qualification:

• Master's AND 7+ years' experience, or Bachelor's AND 9+ years' experience in Computer Science, Computer Engineering, or related field with specialization in Generative AI - LLMs/natural language processing/computer vision/multimodal analysis/deep learning/machine learning/Data Science
• Strong hold on Data Structures, algorithmic problem solving and proficiency in software development/engineering skills (Python/Java/C#)
• Proficiency in Python and open-source tools (e.g., TensorFlow, PyTorch) to develop production-grade quality product 
• Proven Industry experience on large-scale data processing, distributed computing, or cloud platforms and building highly performant production solutions
• Knowledge of Generative AI suite, transformer-based and diffuser-based models (e.g., BERT, GPT, T5, Llama, Stable diffusion) and LLMs
• Proficiency in Agile development practices and Continuous Integration/Continuous Deployment (CI/CD)
• Experience with cloud platforms (e.g., Azure, AWS) and distributed computing
• Design and build end-to-end high performance ML workloads covering model training, data analysis, model serving and model evaluation
• Excellent verbal and written communication skills and ability to work independently and collaboratively

Preferred Qualifications: 

• Training & fine-tuning experience on large data
• Experience with statistical analysis and data visualization tools
• Good understanding of statistics, linear algebra, and probability theory

#IDCAIPHiring

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.

• Build sophisticated Evaluation framework for cutting-edge deep learning models, including LLMs, SLMs, RAG, fine-tuned, distilled models and Generative AI applications such as Co-pilots, Agentic frameworks
• Design and develop the next generation of Azure AI's evaluation platform by integrating advanced AI evaluation solutions into production, with a strong emphasis on building a highly performant, scalable, reliable, and high-quality distributed system
• Research, design, implement State-of-the-art evaluation frameworks to assess model performance across diverse metrics, including quality, latency, cost, robustness and fairness
• Engage in sophisticated prompt engineering techniques to optimize and tailor model outputs for various real-world applications and use cases
• Design and build end-to-end pipelines covering model training, data analysis, model serving and model evaluation
  
• Build and Utilize CI/CD pipelines to manage the build, release, deployment, and test automation processes for AI models, ensuring seamless integration into production systems and maintaining high-quality standards
• Collaborate with cross-functional teams, including researchers, data scientists, software engineers, and product managers
• Implement new product features and evaluation metrics
  
• Embody our  and