Senior AI Engineer, Post-Training
Hybrid (San Francisco, CA; New York City, NY)$242.3k - $285kFull-timePosted 4w ago
About the role
Senior AI Engineer focused on post-training and productionizing open-weight language models for Carta Law, embedded in Carta's ML Engineering team. End-to-end ownership of model development, post-training, evaluation, serving, and agent/tooling systems in a legal tech context.
Responsibilities
- Post-train open-weight language models on proprietary legal data, owning the model development lifecycle end-to-end, from data, objective design, and base-model selection through training, evaluation, and iteration.
- Apply training techniques such as supervised fine-tuning, preference optimization, reinforcement learning, and related methods with careful attention to reward and grader design, model behavior, and evaluation.
- Build and improve training datasets and data pipelines, including labeling guidance, model-generated data, and human feedback loops with domain experts.
- Own the training stack needed to run experiments reliably, using managed or self-hosted infrastructure, and understand distributed training to diagnose and optimize runs.
- Build and operate production systems for models including model serving, agents, evaluation pipelines, and surrounding tooling and infrastructure.
- Partner with product and agent engineers on model/system co-design, deciding what belongs in the model versus the agent harness, tools, context, and workflow.
- Work directly with lawyers and domain experts to translate real workflows into model, data, and evaluation decisions.
Qualifications
- Hands-on experience with LLM post-training using PyTorch or equivalent frameworks.
- Experience across training, evaluation, and inference systems; comfortable building product around the model (agents, tools, services, production infra).
- Ability to work across model and product engineering problems and stay current on open-weight models and post-training techniques.
- Track record of owning model development or post-training work in applied settings and shipping AI systems to real users.
- Ability to turn ambiguous problems into tractable technical work and drive projects from idea to production with limited guidance.
- Strong judgment on model selection, data, training objectives, and evaluation; ability to defend decisions with data and communicate across teams.
- Ambitious experience in AI, applied research, or adjacent engineering roles with ownership of models or systems and measurable impact.
Skills
Required:LLM post-trainingPyTorchTraining data pipelinesProduction systemsDistributed trainingProduct & model co-designDomain collaboration
Benefits
- Competitive salary and equity, exceptional benefits, and commissions where applicable.
Last updated Sep 23, 2026. Interested? Apply on the company site.
About Carta
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