Alma is hiring the best AI engineer in the world to join our world-class engineering team. Every new hire is going to raise the bar and that’s how we are able to deliver the best AI native product ever seen in legal tech space.
Our entire team works between 9 am and 8 pm Pacific Time and 5 days a week. We try to leave the weekend to our team to recharge and spend time with their family.
👋🏼 Hello! We’re ALMA
Backed by leading VCs such as Bling Capital, Forerunner, Village Global, NFX, Conviction, MVP Ventures, NEA and Silkroad Innovation Hub, Alma is a LegalTech startup on a mission to transform the immigration industry. By combining the expertise of seasoned attorneys with AI/ML, we streamline the complex immigration process for individuals and businesses. Our comprehensive platform and dedicated legal team provide clients with a seamless experience, empowering them to navigate the intricate world of immigration with confidence.
🚀 Why you should join ALMA
You will have the opportunity to work alongside mission-driven founders who are determined to make immigration easy. From day 1 you will be solving challenging & interesting problems by leveraging cutting-edge AI research and technology. You will be working with our CTO, a seasoned tech visionary with years of leadership experience at Uber and other established startups, where you'll have the chance to greatly expand your knowledge and skills under his expert mentorship.
🧠 Founding
Team
The founding team has an extensive background in the legal industry, consulting, and building ML platforms.
- Shuo - CTO & Cofounder: Shuo built the ML Platform (Michelangelo) at Uber for 5+ years after which he was the head of AI & ML team at a SupportLogic (a series B startup using predictive & generative AI for customer support).
- Aizada - CEO & Cofounder: Aizada is a graduate of Harvard Law School, an attorney with 7+ years of experience including working at a top law firm such as Cooley and an ex-McKinsey consultant.
- Assel - CPO & Cofounder: Assel is a graduate of Harvard Business School and has 7 years of experience building products at FinTechs such as SoFi and Step and at large financial institutions when working at Ernst & Young.
🔍
What we're looking for
We are looking for a highly-skilled and ambitious AI engineer with 2+ years of LLM experience such as pre-training, mid-training, post-training, inference and building agentic workflow. You will own the AI products end-to-end and trail blaze the path of content generation in legal tech using AI. We need you to be in the 99th percentile of having a “can-do” attitude.
✅ Responsibilities
- Work closely with the founding team and early customers to build and ship AI-native products.
- Translate complex AI research into actionable solutions that deliver measurable business value. Ensure that AI initiatives are aligned with business objectives and deliver impactful results.
- Design & implement LLM-powered products, such as prompting, agents, experimentation, LLM Ops, measuring quality & performance.
- Evaluate and productize various types of LLMs for our product use cases
- Research and stay current with the latest news, tooling, and techniques in NLP such as advanced prompting & chaining, function calling, embeddings, evaluations, building agents, distilling reasoning, etc.
- Own your work end-to-end and integrate the research into our product
🛠 Role Requirements
- MS/Phd in Computer Science, Artificial Intelligence, Machine Learning, or related fields.
- 2+ years of professional experience in LLMs with a proven track record of leading successful AI projects.
- Strong background in applied AI/ML research and development, with publications in top-tier conferences and journals.
- Strong strategic thinking and problem-solving abilities, with a focus on practical application and business impact.
- Located in the San Francisco Bay Area.
- Experience building and shipping applications built on top of LLMs into production and evaluating & improving performance over time after deployment.
- Experience with LLM Ops & tooling (e.g. vector databases, prompt ops).
- Well-developed sense through experience of what works and doesn’t work when building applications on top of LLMs.
⭐️ Nice-to-haves
- Experience working in a small startup environment (Seed or Series A).
