Sr Principal AI Software Engineer - ML & AI Innovation

Position Overview

The Senior Principal AI/ML Software Engineer is responsible for evaluating, integrating, and optimizing cutting-edge technologies for AI/ML infrastructure, focusing on achieving low latency, high throughput, and efficient resource utilization for both model training and inference at scale. This role guides key strategic decisions related to Oracle Cloud’s AI infrastructure offerings, spearheads the design and implementation of scalable orchestration for AI/ML workloads—including incorporating the latest research in generative AI and large language models—and leads initiatives such as Retrieval-Augmented Generation and model fine-tuning. The ideal candidate will design and develop scalable, GPU-accelerated AI services using tools like Kubernetes and Python/Go, and possess strong programming skills, deep expertise in deep learning frameworks, containerization, distributed systems, and parallel computing along with a comprehensive understanding of end-to-end AI/ML workflows.

Key Responsibilities

• Evaluate, integrate, and optimize state-of-the-art technologies across the stack for latency, throughput, and resource utilization for training and inference workloads.
• Guide strategic decisions around Oracle Cloud’s AI infrastructure offerings.
• Design and implement scalable orchestration for serving and training AI/ML models, including model parallelism and performance optimization across the AI/ML stack.
• Explore and incorporate contemporary research on generative AI, agents, and inference systems into the LLM software stack.
• Lead initiatives in generative AI systems design, including Retrieval-Augmented Generation (RAG) and LLM fine-tuning.
• Design and develop scalable services and tools to support GPU-accelerated AI pipelines using Kubernetes, Python/Go, and observability frameworks.

Required Qualifications

• Bachelor’s, Master’s, or Ph.D. in Computer Science, Engineering, Machine Learning, or a related field (or equivalent experience).
• Experience with machine learning and deep learning concepts, algorithms, and models.
• Proficiency with orchestration and containerization tools such as Kubernetes, Docker, or similar.
• Expertise in modern container networking and storage architecture.
• Experience in orchestrating, running, and optimizing large-scale distributed training/inference workloads.
• Deep understanding of AI/ML workflows, including data processing, model training, and inference pipelines.
• Familiarity with parallel computing frameworks and paradigms.
• Strong programming skills and proficiency in major deep learning frameworks.

Benefits & Perks

• Compensation: US hiring range in USD from $96,800 to $251,600 per annum; may be eligible for bonus, equity, and compensation deferral.
• Medical, dental, and vision insurance (including expert medical opinion).
• Short term disability and long term disability coverage.
• Life insurance and AD&D, with supplemental plans available for employees, spouses, and children.
• Health care and dependent care Flexible Spending Accounts.
• Pre-tax commuter and parking benefits.
• 401(k) Savings and Investment Plan with company match.
• Paid time off with flexible vacation policies and accruals based on employment terms.
• 11 paid holidays and 72 hours of paid sick leave (with a carryover cap of 112 hours).
• Paid parental leave and adoption assistance.
• Employee Stock Purchase Plan.
• Financial planning and group legal services.
• Voluntary benefits including auto, homeowner, and pet insurance.