Member Of Technical Staff Machine Learning Engineer (AI)

TL;DR

Member of Technical Staff – Machine Learning Engineer (AI): Designing, developing, and implementing machine learning models for high-performance recommendation systems and personalized feeds with an accent on optimizing user engagement, retention, and personalization. Focus on leveraging large language models (LLMs) to create scalable, intelligent solutions for content understanding, user engagement, and relevance ranking.

Location: Mountain View, United States. Employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) of that location.

Salary: USD $119,800 – $304,200 per year

Company

hirify.global is a division of Microsoft focused on building and integrating artificial intelligence systems across various products and services, aiming to make AI accessible to all.

What you will do

• Design, develop, and implement machine learning models for high-performance recommendation systems and personalized feeds.
• Leverage large language models (LLMs) to create scalable, intelligent solutions for content understanding and user engagement.
• Drive data-driven experimentation using A/B testing, advanced analytics, and statistical techniques.
• Develop and optimize pipelines, tools, and infrastructure for real-time decision-making and personalization.
• Mentor team members and foster collaboration within cross-functional teams, including product managers and designers.
• Stay informed on emerging trends in AI and machine learning to drive continuous innovation.

Requirements

• Bachelor’s Degree in Computer Science, or related technical discipline.
• 4+ years of technical engineering experience with coding in languages including C, C++, C#, Java, JavaScript, or Python.
• 3+ years of experience building and deploying ML models in production environments.
• Strong coding skills in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow).
• Familiarity with data processing tools (e.g., Spark, Pandas) and cloud platforms (e.g., Azure, AWS).
• Experience with classification, recommendation, or personalization systems.

Nice to have

• Experience using large language models (LLMs) for machine learning and AI applications.
• Hands-on experience in growth engineering, driving improvements in user acquisition, engagement, and retention.
• Expertise in personalization strategies and user behavior modeling.
• Strong problem-solving skills and excellent communication abilities.
• Ability to work in a fast-paced environment and manage multiple priorities.

Culture & Benefits

• Embody a culture of inclusion, respect, integrity, and accountability.
• Come together with a growth mindset to empower others and achieve shared goals.
• Certain roles may be eligible for benefits and other compensation.