AI/ML Support Engineer
- Hirextra Inc.
31 Days Ago
NA
W2
Baton Rouge-LA
5-8 Years
Required Skills: compute concepts, including virtualization, containerization, operating systems, system administration, GCP, AWS, Azure, AI/ML services, Vertex AI, Dialogflow, Gemini, Machine Learning model development and deployment, PyTorch, Tensorflow, Jax, Ray, TPUs, GPUs, encoders, decoders, transformers, Google Machine Learning Engineer certification, Google Cloud Associate Cloud Engineer certification, ACE Certification
Job Description
AI/ML Support Engineer (Junior candidates) – Super urgent role
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.
