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Together AI

Runs cloud infrastructure for open AI models

Forward Deployed Engineer - Inference & Post-Training

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeSingaporeIn-person

About the Job

Requirements

  • Must be a permanent resident or citizen of Singapore.
  • Have 5 or more years of experience in a technical role, focused on inference systems, open-source large language model deployment, or post-training workflows.
  • Have expert-level, hands-on experience with inference engines such as vLLM, TensorRT-LLM, or SGLang, and be able to diagnose and resolve performance issues at the engine level.
  • Have deep knowledge of key-value cache tuning, speculative decoding, tensor parallelism, pipeline parallelism, and quantization techniques.
  • Have hands-on experience with fine-tuning and post-training pipelines, including LoRA, supervised fine-tuning, direct preference optimization, reinforcement learning from human feedback, and group relative policy optimization, and be able to advise on system design.
  • Have broad knowledge of state-of-the-art open-source models and sound judgment in selecting models for specific customer use cases, hardware profiles, and performance targets.
  • Have strong Python skills and be comfortable working in production environments.

Responsibilities

  • Select, configure, and optimize inference engines based on hardware, model architecture, and workload profiles.
  • Develop configuration updates to support critical proofs of concept and benchmarks and optimize customer deployments; tune key-value cache, apply speculative decoding, determine optimal tensor parallelism, and select quantization strategies to meet throughput and latency targets.
  • Run hands-on reinforcement learning training and optimize system design; guide customers through LoRA, supervised fine-tuning, direct preference optimization, reinforcement learning from human feedback, and group relative policy optimization pipelines from experimentation through production.
  • Serve as the primary technical point of contact for aligned strategic accounts by monitoring and optimizing endpoint configurations, helping customers use the platform effectively, and collaborating to meet critical milestones.
  • Align directly with strategic customers during onboarding and ensure suitable inference and post-training configurations are in place from day one to improve time-to-value.
  • Surface field insights to influence the software and model roadmap, contribute to the product to support customer requirements or improve user experience, and drive early feature and research adoption with strategic customers.

About the Company

Together AI

Runs cloud infrastructure for open AI models

Together AI runs cloud infrastructure for developers and businesses that train, customize, and deploy AI models, with a focus on open models that customers control. Its platform combines model hosting with tools for adapting models to tasks such as coding assistants, customer support, and image generation. Developers call models through an API, reserve dedicated capacity for steady workloads, or rent GPU clusters for training, while the company charges for model usage and computing resources. Teams also fine-tune models on their own data and deploy the results through the same platform without building a separate serving system. Together AI was founded in 2022 and is based in San Francisco.

Company size
201-500
Company stage
Series C
Total funding
$1.3B
Headquarters
San Francisco, CA
Founded
2022

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