[Remote] Machine Learning Engineer

About the Role

As a Machine Learning Engineer at Oracle, you will build scalable, reliable, and production-ready ML systems. Oracle is investing heavily in Generative AI, requiring a strong understanding and experience in leveraging Large Language Models. Your expertise will be pivotal in developing Conversational AI solutions and other cutting-edge Machine learning techniques to enhance user experience with AI/ML/GenAI capabilities. You will collaborate with cross-functional teams, including product managers, software engineers, and operations teams, to simplify business requirements into scalable solutions. The ideal candidate is highly technical in ML and AI, can lead across the full stack, and possesses good product sense and business understanding.

Key Responsibilities

• Proficient in creating detailed design specifications and writing elegant code.
• Lead the incubation of new initiatives, architect scalable solutions, and drive strategic technology choices to develop and deliver AI/ML capabilities.
• Develop high-quality, scalable, and efficient software solutions that integrate generative AI capabilities.
• Design, develop, test, and deploy Machine learning models, including large-language models.
• Build pipelines at scale for batch and real-time use cases.
• Leverage third-party and in-house ML tools & OCI platform to develop reusable, highly performant machine learning systems with low-latency serving and reliable means to update/re-train ML models.
• Work collaboratively with cross-functional partners, identify opportunities for business impact, understand and prioritize requirements for machine learning systems and data pipelines, drive engineering decisions, and quantify impact.
• Communicate continually with project teams and explain progress on development efforts.
• Ensure quality of work through development standards and QA procedures.
• Keen on improvising technical solutions and processes emphasizing discovery through doing, iteration, and feedback loops.

Requirements & Tech Stack

• Proficient in building distributed systems, containerization, orchestration, and cloud-native architectures.
• Familiarity with Python and ML frameworks such as PyTorch, TensorFlow, etc., is a must.

Qualifications

• Strong understanding and experience in leveraging the capabilities of Large Language Models.
• Ability to lead across the full stack.
• Good product sense and business understanding.