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Salary: USD 270,000 - 300,000 / annual
Together AI is seeking a Forward Deployed Engineer (FDE) focused on Post-Training to serve as a hands-on technical partner to strategic customers building differentiated AI models through fine-tuning and reinforcement learning on open-source foundations.
You will work alongside Solutions Architects as the deep-domain specialist in post-training, guiding customers through data strategy, algorithm selection, experiment design, evaluation, and compute sizing. Your responsibilities include:
• Data Strategy: Help customers define and execute data strategies for model post-training, diagnose data quality issues limiting performance, and recommend data generation approaches for scaling.
• Algorithm Selection: Recommend the optimal post-training approach for each customer use case.
• Experiment Design & Hyperparameter Tuning: Design well-controlled experiments with robust tracking; diagnose training instabilities, reward hacking, and performance regressions.
• Evaluation: Build evaluation frameworks including task-specific benchmarks, LLM-as-judge pipelines, and held-out test sets to ensure reproducible alignment with production success metrics.
• Model Selection: Guide base model selection methodology and conduct baseline quality evaluations to inform post-training objectives. Stay current with newly released open-source models relevant to post-training.
• RL Workload Sizing: Scope and size RL and fine-tuning workloads; partner with sales and capacity teams on deal shaping and forecasting.
• Strategic Customer Alignment: Serve as primary post-training technical contact for strategic accounts, leading technical execution from scoping through production.
• Product & Research Feedback: Shape the fine-tuning and RL product roadmap with field insights; contribute code, recipes, and reference implementations; drive early adoption with strategic customers.
Your work directly impacts customer success, company growth, and platform hardening.
REQUIREMENTS:
• 5+ years in a technical role (ML engineering, Applied AI, Forward Deployed Engineering, or Solutions Architecture) with recent hands-on post-training LLM experience
• Expert-level, hands-on experience with fine-tuning and/or RL for LLMs, including SFT, LoRA, DPO, and RL methods (GRPO, PPO, etc.)
• Strong track record designing experiments, running ablations, and building evaluations that distinguish real improvement from noise
• Proven ability to build and iterate on training datasets
• Broad knowledge of state-of-the-art open-source models with strong judgment on base model selection for customer requirements
• Strong Python proficiency; comfortable working in production environments
• Experience leading complex, customer-facing technical projects with exceptional project management and communication skills; ability to work in highly cross-functional environments
About Together AI
AI / Data / Infrastructure — cloud platform for open-source and generative AI model training and inference.
