Forward Deployed Engineer (Inference & Post-Training)
Together AI · San Francisco
CHECKED 1H AGO
Infrastructureonsitesenior$270k–$300k
At a glance
Highlights
- Serve as hands-on partner to strategic customers deploying AI at scale.
- Guide tailored efforts to ensure successful platform adoption and growth.
- Influence software and model roadmap with insights surfaced from field.
What they offer
- Startup equity
- Health insurance
- Flexible remote work
Ideal candidate
Hands-on engineer with 5+ years around production AI who loves working directly with customers. Deeply curious about performance, pragmatic, and motivated to turn complex deployments into customer success.
Requirements
- 5+ years in technical role focused on inference systems, open-source LLM deployment, or post-training workflows
- Expert-level hands-on experience with inference engines with ability to diagnose engine-level performance issues
- Deep knowledge of KV cache tuning, speculative decoding, tensor/pipeline parallelism, and quantization
- Hands-on experience with LoRA, SFT, DPO, RLHF, and GRPO pipelines and system design guidance
- Broad knowledge of state-of-the-art open-source models and judgment on model selection
- Strong Python skills with comfort working in production environments
- remote policy
- Flexible remote work
Lab profile
About Together AI
AI-native cloud for training and inference on large-scale GPU infrastructure for AI apps and agents.
What they build
- AI-native cloud platform
- GPU clusters for training and inference
- Platform for AI applications and agents
Known for
- Operating large-scale GPU fleets
- Automated infrastructure at massive scale
- Multi-site data center deployment
Key facts
- Over 1M developers
- Operates one of the world's largest GPU fleets
- Infrastructure managing tens of thousands of GPUs