Forward Deployed Engineer – Inference, Post-Training, Mandarin Speaking

🔥 22 hours ago

🇸🇬 Singapore – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

👷🏻‍♀️ Engineer

👻 Ghost score 12%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Together AI

WebsiteLinkedInAll Job Openings

11 - 50 employees

🤖 Artificial Intelligence

☁️ SaaS

🏢 Enterprise

💰 $102.5M Series A on 2023-11

Artificial Intelligence • SaaS • Enterprise

Together AI is a company focused on accelerating the generative AI lifecycle by providing solutions for training, fine-tuning, and deploying AI models. They offer an end-to-end platform for leveraging pre-trained models, adapting them to specific needs, or building custom models from scratch. Together AI supports AI compute solutions with its Together Inference engine and Together GPU Clusters, allowing for scalable and efficient AI operations. Their infrastructure is powered by advanced GPUs and optimized software stacks for high performance in AI tasks.

📋 Description

• Select, configure, and optimize inference engines based on hardware, model architecture, and workload profile • Develop configuration updates to win critical POCs and benchmarks and optimize customer deployments • Tune KV cache, apply speculative decoding, determine optimal tensor and pipeline parallelism, and determine quantization strategies to meet throughput and latency targets • Drive hands-on RL training runs and optimize system design • Guide customers through LoRA, SFT, DPO, RLHF, and GRPO pipelines from experimentation through production • Act as the primary technical point of contact for strategic accounts • Monitor and optimize endpoint configurations and help customers maximize platform value • Collaborate with customers to achieve critical milestones • Establish direct alignment with strategic customers during onboarding • Ensure appropriate inference and post-training configurations are in place from day one • Surface field insights to influence the software and model roadmap • Contribute to the product to support customer requirements and improve the customer experience • Drive early feature and research adoption with strategic customers

🎯 Requirements

• Must be a permanent resident or citizen of Singapore • 5+ years in a technical role, with a strong focus on inference systems, open-source LLM deployment, or post-training workflows • Expert-level, hands-on experience with inference engines such as vLLM, TensorRT-LLM, or SGLang • Ability to diagnose and resolve performance issues at the engine level • Deep knowledge of KV cache tuning, speculative decoding, tensor parallelism, pipeline parallelism, and quantization techniques • Hands-on experience with fine-tuning and post-training pipelines, including LoRA, SFT, DPO, RLHF, and GRPO • Ability to advise on system design • Broad knowledge of state-of-the-art open-source models • Strong judgment on model selection for specific customer use cases, hardware profiles, and performance targets • Strong Python skills • Comfortable working in production environments

🏖️ Benefits

• Competitive compensation • Startup equity • Health insurance • Other benefits • Flexibility in terms of remote work

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