Research Engineer Inference Specialist

1 week ago


Palo Alto, California, United States Acceler8 Talent Full time

Unlock AI Innovation as a Member of Technical Staff, Research Engineer (Inference)

Acceler8 Talent is seeking a highly skilled Research Engineer (Inference) to join our team of AI innovators. As a key member of our technical staff, you will play a pivotal role in optimizing and deploying state-of-the-art models for real-world applications.

About the Company

Our AI studio is renowned for its groundbreaking work in developing and deploying highly effective language models. With a strong foundation in model alignment and fine-tuning, we are now focused on scaling our technology for enterprise use cases. Our team is well-funded and equipped with cutting-edge resources, offering a unique environment for those passionate about pushing AI boundaries.

About the Role

As a Research Engineer (Inference), you will be responsible for optimizing AI models for enterprise deployment, ensuring they perform efficiently under varying conditions. Your work will focus on reducing latency, improving throughput, and maintaining model performance during inference. Engineers in this role should have a deep understanding of the trade-offs in model inference, including balancing hardware constraints with real-time processing demands.

What We Offer

  • Competitive compensation aligned with your experience and contributions.
  • Unlimited paid time off and flexible parental leave.
  • Comprehensive medical, dental, and vision coverage.
  • Visa sponsorship for qualified hires.
  • Professional growth opportunities through coaching, conferences, and training.

Key Responsibilities:

  • Optimize and deploy large language models (LLMs) for inference across cloud and on-prem environments.
  • Utilize frameworks like ONNX, TensorRT, and TVM to accelerate model performance.
  • Troubleshoot complex issues related to model scaling and performance.
  • Collaborate with cross-functional teams to refine and deploy inference pipelines using PyTorch, Docker, and Kubernetes.
  • Balance competing demands, such as model accuracy and inference speed, in enterprise settings.

If you have experience with LLM inference, model optimization tools, and infrastructure management, this role aligns perfectly with your skills.


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