Sr. AI Machine Learning Engineer

A10 Networks, Inc; San Jose (CA); Presencial; USD 110 000 - 145 000; Tempo integral

Resumo da oferta

A10 Networks, Inc. is seeking a Sr. AI Machine Learning Engineer specializing in Large Language Models (LLMs) to join our team.

You will help improve safety, reliability, and performance of AI systems while collaborating with researchers and product teams. Responsibilities include designing safety frameworks for LLMs, applying risk mitigation and adversarial testing, and tuning models with domain data; strong Python and DL framework skills are essential.

Qualificações

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field.
• Proven experience developing and deploying Large Language Models (LLMs) focusing on architectures like GPT, BERT, and variants.
• Strong Python programming and deep learning framework experience (TensorFlow or PyTorch).
• Knowledge of distributed training techniques and cloud platforms (AWS, Azure, Google Cloud).
• Excellent problem-solving skills and ability to work independently and in a team.

Responsabilidades

• Assist in designing end-to-end safety-focused frameworks for LLMs.
• Develop risk mitigation techniques and safe inference strategies.
• Identify vulnerabilities and contribute to adversarial testing and bias mitigation.
• Collaborate with cross-functional teams to integrate safety into AI workflows.
• Design and optimize LLM architectures for performance and scalability.
• Fine-tune pre-trained LLMs on domain-specific data to improve task performance.
• Stay updated with latest DL research and techniques.
• Demonstrate strong software engineering and prototyping skills.

Conhecimentos

LLMs

Python

TensorFlow

PyTorch

Distributed training

Cloud platforms

Problem solving

Communication

Formação académica

Bachelor's or Master's in CS/EE

Ferramentas

TensorFlow

PyTorch

AWS

Azure

Google Cloud

Descrição da oferta de emprego

Sr. AI Machine Learning Engineer

Position Overview

We are looking for a talented and experienced Deep Learning Engineer specializing in Large Language Models (LLMs) to join our dynamic team. In this role, you will play a pivotal part in enhancing the reliability, safety, and performance of AI models and systems. You will work closely with AI researchers and product teams to drive cutting-edge advancements in AI safety and responsible AI solutions.

Responsibilities

• Assist in designing and implementing end-to-end safety-focused frameworks for LLMs

• Develop and apply risk mitigation techniques, including safe inference strategies to ensure reliable AI behavior

• Identify vulnerabilities in AI systems and contribute to adversarial testing, bias detection, and mitigation strategies

• Collaborate with cross-functional teams to integrate safety mechanisms into AI workflows and pipelines

• Design and optimize LLM architectures to improve performance, scalability, and efficiency

• Fine-tune pre-trained LLMs on domain-specific datasets to improve task performance

• Stay up to date with the latest research papers, techniques, and advancements in deep learning and related fields

• Strong software engineering and programming skills, and ability to quickly develop working prototypes from research ideas

Requirements

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field

• Proven experience in developing and deploying Large Language Models (LLMs), with a focus on architectures such as GPT, BERT, and their variants

• Strong programming skills in Python and experience with deep learning frameworks such as TensorFlow or PyTorch

• Knowledge of distributed training techniques and experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud)

• Excellent problem-solving skills and ability to work independently and in a team environment

• Strong communication and collaboration skills

AI Use Guidelines for Interviews:Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.

Targeted compensation guideline: $110,000 - $145,000. Compensation will vary based on number of factors, including market demand for specific skills, role type, job level, and individual qualifications. Final salary offers are determined by considerations including, but not limited to, subject matter expertise, demonstrated skill level, relevant experience, geographic location, education, certifications, and training.