Sr. AI Machine Learning Engineer

A10 Networks, Inc.; San Jose (CA); On-site; USD 110,000 - 145,000; Full time

Job summary

A10 Networks, Inc. is seeking a talented Deep Learning Engineer specializing in Large Language Models (LLMs) to enhance AI model performance and safety. You'll collaborate with AI researchers to drive advancements in AI safety.

The ideal candidate will have a degree in Computer Science or related field, proven experience with LLMs, and strong programming skills in Python. Targeted compensation is between $110,000 - $145,000 based on qualifications and market factors.

Qualifications

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

Responsibilities

• Assist in designing and implementing end‑to‑end safety‑focused frameworks for LLMs.
• Develop and apply risk mitigation techniques for reliable AI behavior.
• Identify vulnerabilities in AI systems and contribute to adversarial testing.

Skills

Deep Learning

Large Language Models (LLMs)

Python

TensorFlow

PyTorch

Distributed Training Techniques

Cloud Computing

Education

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

Job description

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.

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.

Compensation

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.