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About the Role
As an AI Engineer on the ML Engineering team, embedded in Carta Law, you will have end-to-end ownership across model development and applied AI, from post-training and evaluation through model serving and the agents and systems built around those models. You will lead technically complex, model-centric projects and serve as a multiplier for your team.
Responsibilities
- Post-train open-weight language models on proprietary legal data, owning the model development lifecycle end-to-end.
- Apply the right training techniques for the problem, including supervised fine-tuning, preference optimization, and reinforcement learning.
- Build and improve training datasets and data pipelines, including labeling guidance and human feedback loops.
- Own the training stack needed to run experiments reliably.
- Build and operate the systems that take models into production, including model serving and agents.
- Partner with product and agent engineers on model/system co-design.
- Work directly with lawyers and other domain experts to translate real workflows into model, data, and evaluation decisions.
Requirements
- Hands-on experience with LLM post-training using PyTorch or equivalent frameworks.
- Understand the training, evaluation, and inference systems around LLMs.
- Comfortable building the product around the model, including agents, tools, services, and production infrastructure.
- Ability to work across model and product engineering problems.
- Stay current on open-weight models and post-training techniques.
- Owned model development or post-training work in applied settings.
- Built AI systems around models that shipped to real users.
- Ability to turn ambiguous product or model problems into tractable technical work.
- Pragmatic trade-offs across research and engineering.
- Drive projects from idea through production with minimal guidance.
- Strong judgment on model selection, data, training objectives, and evaluation.
- Ability to make and defend decisions with data.
- Communicate decisions clearly across technical and domain teams.
- Meaningful ownership of the models or systems built.
- Experience spans both model-level training work and the product and engineering systems around it.
Skills
- LLM post-training
- PyTorch
- Model serving
- Agent development
- Data pipelines
- Supervised fine-tuning
- Preference optimization
- Reinforcement learning
Location
- San Francisco, CA
- New York City, New York
Work Type
- Full-time
Experience Level
- Senior
Salary/Compensations
- $242,250 - $285,000
Benefits
- Equity for all full-time roles
- Exceptional benefits
- Commissions plans (for applicable roles)
About the Company
- Carta is the connected platform and AI-native ecosystem for private capital.
- Carta brings together the software, services, and legal infrastructure that founders use to manage equity, fund managers use to run administration and reporting, and legal teams use to close transactions.
- Trusted by 55,000 companies and 1.8M+ equity holders in 160+ countries, and 10,000 funds and SPVs representing $250B+ in assets under management, Carta is transforming how private capital operates.
- Recognized by Fortune, Forbes, Fast Company, Inc. and Great Places to Work.
- Cartans are helpful, relentless, unconventional and kind; representing Carta’s Identity Traits.
- They work collaboratively and cross functionally to challenge the status quo; working towards a common goal of creating more owners in the private markets.
Equal Opportunity
- We are an equal opportunity employer and are committed to providing a positive interview experience for every candidate.
- If accommodations due to a disability or medical condition are needed, please connect with the talent partner via email.
- Carta uses E-Verify in the United States for employment authorization.