AI/ML Support Engineer

Experience: Must have 10+ years of experience, Ideal candidates should possess a strong foundation in AIML, machine learning, and natural language processing, with a specific emphasis on data analysis, data pipelines, and model deployment. They should be capable of troubleshooting model-related issues, optimizing model performance, and providing expert support for various AIML platforms.

Technical Skills: Compute Fundamentals: Demonstrates a deep understanding of compute concepts, including virtualization, containerization, operating systems, and system administration.

Cloud Technologies: Experience with cloud platforms like Google Cloud Platform, AWS, and Azure, including their AI/ML services.

Generative AI Experience with LLM and Generative AI and Google Cloud Products and services (e.g Vertex AI, Dialogflow, Gemini)

ML Development: Experience with Machine Learning model development and deployment.

AIML Frameworks: Experience with frameworks for deep learning (e.g. PyTorch, Tensorflow, Jax, Ray, etc.), AI accelerators (e.g. TPUs, GPUs), model architectures (e.g. encoders, decoders, transformers), and using machine learning APIs.

Experience: Troubleshooting Code Experience: 2 years of experience reading code in a general purpose coding language (e.g., Java, C, C++, Python, Shell, Go or JavaScript, etc.) or in system design.

AIML Experience: +2 Experience with Machine Learning model development and deployment.

Troubleshooting Experience: 3+ years of experience in troubleshooting, diagnosing, and resolving complex issues.

Support Experience: Familiarity with support methodologies, case lifecycles, and analytical skills for breaking down issues.

Certifications Google Machine Learning Engineer certification is desired. *

• Google Cloud Associate Cloud Engineer (ACE) certification is required.