This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Principal Machine Learning Engineer based in the United States. 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. Accountabilities You will drive the technical vision and development of advanced machine learning solutions, ensuring that AI-powered platforms deliver reliable, scalable, and high-performance capabilities. Your responsibilities will include: Act as a technical thought leader, shaping innovative machine learning strategies and product solutions across multiple platforms. Design, develop, and launch strategic machine learning and generative AI capabilities that support business-wide innovation. Lead the complete software development lifecycle, including architecture, design, coding, testing, deployment, and ongoing operations. Drive technical discussions, establish engineering direction, and participate directly in design reviews, code reviews, and implementation. Architect and build high-performance, scalable microservices, including synchronous and asynchronous web services. Develop real-time online inference solutions for complex machine learning models using technologies such as NVIDIA Triton, TensorRT, and mixed-precision computing. Contribute to AI initiatives involving intelligent agents, retrieval-augmented generation, knowledge bases, data mining, anomaly detection, and LLM fine-tuning. Build resilient distributed systems and cloud-based architectures capable of supporting demanding workloads. Mentor and develop other engineers, strengthen technical capabilities, and foster a collaborative engineering culture. Establish high standards for technical quality, operational excellence, system reliability, and scalability. Identify opportunities to improve engineering processes, workflows, system performance, and operational practices.

Requirements

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. Preferred qualifications: 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.

Benefits

Annual salary range of $170,000–$240,000 USD, depending on qualifications, experience, and geographic region. Additional benefits package. Opportunity to work with highly skilled engineers on advanced AI and machine learning technologies. Exposure to innovative projects involving generative AI, intelligent agents, distributed systems, and network intelligence. Opportunities to provide technical leadership, mentor engineers, and influence product and platform development. Inclusive and collaborative working environment that values diverse perspectives and encourages professional growth. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.