AI/ML Support Engineer
- Hirextra INC.
19 Hours Ago
NA
W2, C2C
Remote
7-20 Years
Required Skills: LLM
Job Description
This profile outlines the desired skills and experience for an AIML Support Engineer, empowering teams to effectively identify and recruit qualified candidates. 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 GCP, 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.
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 GCP, 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 Machine Learning Engineer certification is desired
- Google Cloud Associate Cloud Engineer (ACE) certification is required.
