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Forward Deployed Engineer (Inference & Post-Training)

Location
San Francisco
Compensation
$270k–$300k/yr
Level
senior
Type
full time · Remote OK

Requirements

Experience
5+ years

Benefits

Health Insurance Equity/Stock Options Remote Work

Joblaze summary

In the role of Forward Deployed Engineer at Together AI, the individual will work closely with strategic customers to optimize inference systems and ensure successful deployment of AI models. This position requires deep expertise in inference engine optimization, fine-tuning pipelines, and hands-on experience with various post-training techniques. Ideal candidates will have over five years of technical experience, particularly in open-source LLM deployment, and a strong coding background in Python. Together AI emphasizes collaboration and innovation, making this role suitable for those who thrive in dynamic, research-driven environments.

Joblaze insights

Quick facts

Is the Forward Deployed Engineer (Inference & Post-Training) role remote?
It's hybrid — Together AI expects some on-site time in San Francisco.
What's the salary range?
Together AI lists $270,000–$300,000 for this role.
How much experience is required?
At least 5 years of relevant experience for this Forward Deployed Engineer (Inference & Post-Training) role.
Where is the role based?
Together AI is hiring for this position in San Francisco.
What's the tech stack?
Joblaze extracted these technologies from the posting: TensorRT-LLM, SGLang, LORA, vLLM, AI/ML, DPO.
What seniority level is this role?
Together AI targets senior candidates for this position.
Is this full-time or contract?
Full-time for this Forward Deployed Engineer (Inference & Post-Training) role at Together AI.

From the original posting

About the role

As a Forward Deployed Engineer (FDE) focused on Inference & Post-Training, you will be a hands-on technical partner to our most strategic customers — production AI teams looking to leverage high quality models and do inference at scale. For us, FDE is not a replacement for a Solutions Architect; you will partner with our SAs as a deep-domain specialist in inference optimization, fine-tuning pipelines, and production deployment. As key contributors to both the CX, Engineering, and Sales organizations, FDEs add tremendous value by ensuring we can meet the requirements of our most complex POCs, facilitate successful platform adoption, and guide tailored optimization efforts — directly impacting customer success, company growth, and the hardening of our core platform.

Responsibilities

  • Inference Engine Optimization: Select, configure, and optimize inference engine based on hardware, model architecture, and workload profile
  • Configuration & Performance Tuning: Develop configuration updates to win critical POCs, benchmarks, and optimize customer deployments; tune KV cache, apply speculative decoding, determine optimal tensor parallelism, and determine quantization strategy to hit throughput and latency targets.
  • Post-Training & Fine-Tuning: Drive hands-on RL training runs and optimize system design; guide customers through LoRA, SFT, DPO, RLHF, and GRPO pipelines from experimentation through production.
  • Strategic Customer Alignment: Act as the primary technical point of contact for aligned strategic accounts — monitoring and optimizing endpoint configurations, helping customers get the most out of the platform, and collaborating to ensure we hit critical milestones.
  • Opinionated Onboarding: Establish direct alignment with strategic customers at onboarding; ensure the right inference and post-training configurations are in place from day one to improve time-to-value.
  • Product Feedback Loop: Directly influence our software and model roadmap by surfacing insights from the field. Contribute back to the product where needed to support customer requirements or drive a better experience. Drive early feature and research adoption with strategic logos.

Qualifications

  • Experience: 5+ years in a technical role, with a strong focus on inference systems, open-source LLM deployment, or post-training workflows.
  • Inference Engine Depth: Expert-level, hands-on experience with inference engines (e.g., vLLM, TensorRT-LLM, SGLang); ability to diagnose and resolve performance issues at the engine level.
  • Inference Optimization: Deep knowledge of KV cache tuning, speculative decoding, tensor parallelism, pipeline parallelism, and quantization techniques
  • Post-Training Knowledge: Hands-on experience with fine-tuning and post-training pipelines, including LoRA, SFT, DPO, RLHF, and GRPO; ability to advise on system design
  • Model Landscape Awareness: Broad knowledge of state-of-the-art open-source models and strong judgment on model selection for specific customer use cases, hardware profiles, and performance targets.
  • Coding Proficiency: Strong Python skills; comfortable working in production environments

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancements such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers on our journey in building the next generation of AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $270,000 - $300,000 OTE + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our Privacy Policy at https://www.together.ai/privacy

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