AI Principal Machine Learning Engineer

The AI Principal Machine Learning Engineer will help shape the next generation of intelligent networking solutions through advanced machine learning and generative AI technologies. Working within an AI-focused engineering organization, you will design and deliver innovative capabilities spanning AI agents, retrieval-augmented generation (RAG), knowledge bases, data mining, anomaly detection, and large language model fine-tuning. You will provide technical leadership across the full software development lifecycle, from architecture and implementation to deployment and operations. The role combines hands-on engineering with strategic decision-making, helping build high-performance, scalable, and resilient AI platforms. You will also mentor engineers, influence technical direction, and promote engineering excellence across distributed systems and real-time inference. This is an opportunity to contribute to transformative network intelligence technologies within a collaborative, innovation-driven environment.

The ideal candidate combines deep software engineering expertise with advanced machine learning knowledge and proven technical leadership. You should bring:

• A degree in Mathematics, Computer Science, or a related technical discipline.

• Between 5 and 10 years of experience across the full software development lifecycle, including system design, coding, code reviews, testing, build processes, deployments, and operations.

• Between 5 and 10 years of hands-on Python experience, including advanced language features, libraries, and development practices.

• Strong expertise in designing RESTful APIs, with practical experience using frameworks such as FastAPI.

• Proficiency in Docker, Kubernetes, and modern continuous integration and continuous delivery (CI/CD) practices.

• At least 3 years of experience leading the design and architecture of large-scale distributed systems, preferably within cloud environments such as AWS, Azure, or Google Cloud.

• Previous experience as a technical mentor, technical lead, or engineering team leader.

• A strong understanding of software architecture, scalable microservices, and high-performance computing.

• Excellent problem-solving and analytical skills, with the ability to manage complex technical challenges and optimize system performance.

• Strong communication and collaboration skills, with the ability to influence technical decisions and guide engineering teams.

• A Master's or PhD in Computer Science, or equivalent advanced experience in machine learning.

• Practical experience with machine learning frameworks and platforms such as PyTorch, Amazon SageMaker, NVIDIA Triton, and TensorRT.

• Experience working with NoSQL and document-oriented databases.

• Proven ability to manage large-scale data, optimize processing workflows, and improve system efficiency.

• A strong interest in emerging AI technologies, generative AI, and intelligent systems.