Microsoft Principal Software Engineering Manager - Business & Industry Copilots 

Ireland, Dublin 

379853859

• Knowledge of machine learning algorithms and concepts (e.g., supervised learning, unsupervised learning, deep learning) as applied to generative AI.
• 3+ years of people management experience in software engineering domain.

• 8+ years of professional experience in a technical role developing, training, evaluating and deploying ML solutions at scale for real-world problems

• 8+ years of experience as a software engineer, developing and shipping software in Python, C#, Java or modern language equivalent.

• Familiarity with ML frameworks and libraries like TensorFlow, PyTorch, Scikit-learn, Keras, etc.

• Experience in handling large datasets and working with data processing frameworks (Apache Spark, Hadoop etc.)

• Hands-on experience with cloud platforms like Azure, AWS or GCP for deploying and scaling machine learning models.

• Excellent cross-group and interpersonal skills, with the ability to articulate solutions.

• Bachelors/Master’s degree with relevant course work toward Computer Science, Data Science, Statistics, Machine Learning, Data Mining and equivalent work experience.

Preferred Qualifications:

• Experience in designing and implementing MLOps strategies for model deployment, monitoring, and governance.

• Familiarity in deep learning architectures (Transformers, CNNs, RNNs) and knowledge of Natural Language Processing (NLP)

• Knowledge of containers (Docker) and orchestration tools like Kubernetes.

• Strong analytical mind and a confident decision maker

• Excellent computer science fundamentals in algorithmic design, data structures, and analyzing complexity

• Ability to balance competing demands and adapt to changing priorities

• Lead, mentor, and manage a team of software engineers to design, develop, and implement robust and scalable software applications that utilize generative AI techniques.
• Integrate LLMs and NLP into software solutions for tasks such as content recommendations, summarization, translation, and retrieval.
• Optimize generative AI models and their performance for specific use cases.
• Establish and drive the adoption of good coding standards and patterns.
• Identify opportunities to improve and optimize existing systems using generative AI.
• Stay up-to-date with the latest trends and technologies in generative AI.
• Collaborate with cross-functional teams to deliver high-quality software solutions.