Together AI Logo

Together AI

Forward Deployed Engineer, Post-Training

Posted 13 Days Ago
Be an Early Applicant
In-Office
San Francisco, CA, USA
270K-300K Annually
Senior level
In-Office
San Francisco, CA, USA
270K-300K Annually
Senior level
Lead customer-facing post-training initiatives for large language models, including data strategy, algorithm selection, experiment design, evaluation, model selection, and RL workload sizing. Guide strategic customers from scoping through production, deliver measurable model-quality improvements, contribute code and reference implementations, and provide feedback to product and research teams. Requires deep hands-on expertise with LLM fine-tuning, reinforcement learning, experimentation, evaluation, datasets, open-source models, and production Python engineering.
The summary above was generated by AI
About the role

As a Forward Deployed Engineer (FDE) focused on Post-Training, you will be a hands-on technical partner to our most strategic customers: AI teams using fine-tuning and reinforcement learning to build differentiated models on open-source foundations. FDE does not replace our Solutions Architects. You will work alongside them as the deep-domain specialist in post-training, guiding customers through data strategy, algorithm selection, experiment design, and evaluation, and sizing the compute behind it. You’ll make sure we can deliver on our post-training POCs, drive adoption of our fine-tuning and RL platform, and turn customer goals into measurable gains in model quality. Your work directly affects customer success, company growth, and the hardening of our core platform.

Responsibilities
  • Data Strategy: Help customers define and execute their data strategy for model post-training,  diagnose data quality issues that limit model performance outcomes, and provide recommendations for data generation for post-training scale
  • Algorithm Selection: Recommend the right post-training approach for each use case
  • Experiment Design & Hyperparameter Tuning: Design well-controlled experiments and tracking methods; diagnose training instabilities, reward hacking, and regressions.
  • Evaluation: Build evaluation frameworks with customers, including task-specific benchmarks, LLM-as-judge pipelines, and held-out test sets. Make sure gains are reproducibly aligned with production success metrics.
  • Model Selection: Guide base model selection methodology ahead of post-training efforts and baseline quality evaluations to guide post-training objectives. Interest in self-directed research of newly released open source models, particularly as they relate to post-training.
  • RL Workload Sizing: Scope and size RL and fine-tuning workloads, partner with sales and capacity teams to shape deals and capacity forecasts.
  • Strategic Customer Alignment: Serve as the primary post-training technical point of contact for aligned strategic accounts. Lead technical execution from scoping to production and make sure we hit critical milestones.
  • Product & Research Feedback Loop: Shape our fine-tuning and RL product roadmap with insights from the field. Contribute code, recipes, and reference implementations where needed, and drive early adoption of new features and research with strategic logos.
Requirements 
  • Experience: 5+ years in a technical role in ML engineering, Applied AI, Forward Deployed Engineering, or Solutions Architect, with recent hands-on experience post-training LLMs.
  • Post-Training Depth: Expert-level, hands-on experience with fine-tuning and/or  RL for LLMs, including SFT, LoRA, DPO, and RL (GRPO, PPO, etc)..
  • Experimental Rigor: Strong track record designing experiments, running ablations, and building evaluations that separate real improvement from noise.
  • Data Intuition: Proven ability to build and iterate on training datasets
  • Model Landscape Awareness: Broad knowledge of state-of-the-art open-source models and strong judgment on which base model to post-train for a given customer requirements
  • Coding Proficiency: Strong Python skills; comfortable working in production environments.
  • Experience leading complex, customer-facing technical projects, with exceptional project management and communication skills. Able to work in a highly X-functional environment.
About Together AI

Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month.

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. 

Application Policy

Please read each role carefully and apply to the position best suited to you. Candidates are limited to 6 applications within a 90-day period, and applications beyond that limit will be automatically rejected. You may apply to additional roles 90 days after your last application.

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

Together AI San Francisco, California, USA Office

584 Castro St, #2050, San Francisco, California , United States, 94114

Similar Jobs

11 Minutes Ago
Easy Apply
Hybrid
San Francisco, CA, USA
Easy Apply
154K-264K Annually
Mid level
154K-264K Annually
Mid level
Fintech • Mobile • Software • Financial Services
Lead the Prism engineering team building SoFi’s internal AI productivity platform. Manage and develop software engineers, oversee AI infrastructure such as model harnesses, routing, and evaluations, define the technical roadmap, and partner with internal developer customers to drive platform adoption. The role requires people management, AI developer-tooling expertise, platform engineering experience, and the ability to deliver rapidly in an ambiguous, greenfield environment.
Top Skills: Ai Evaluation FrameworksAi PlatformsLlmsRetrieval-Augmented Generation (Rag)
43 Minutes Ago
In-Office
San Francisco, CA, USA
100K-130K Annually
Entry level
100K-130K Annually
Entry level
Healthtech • Telehealth
Supports clinical and insurance operations by optimizing workflows, analyzing provider performance, coordinating credentialing and enrollment, assisting with payer contracting, monitoring billing and claims performance, and maintaining compliance with CMS, telehealth, and payer requirements. Partners with clinical, product, engineering, data, and external teams to improve reporting, documentation, provider resources, and insurance-program infrastructure.
Top Skills: AIEmr
An Hour Ago
Easy Apply
Hybrid
San Mateo, CA, USA
Easy Apply
150K-170K Annually
Senior level
150K-170K Annually
Senior level
Digital Media • Mobile • Software • Conversational AI
Own and improve the systems, processes, workflows, reporting, and data supporting the company’s go-to-market organization. Manage Salesforce, LeanData, and Gainsight; implement AI-enabled solutions; administer additional GTM technologies; develop dashboards, playbooks, compensation structures, and process documentation; and lead cross-functional initiatives across Sales, Marketing, Customer Success, Finance, and Product.
Top Skills: AIClaudeClayGainsightGongGoogle WorkspaceHubspotLeandataLinkedin Sales NavigatorNooksRingleadSalesforceVercelZoominfo

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account