Applied Scientist (ML)

Mountain View, California, United States Role As an Applied Scientist (ML) at Samaya, you will collaborate closely with our product and engineering teams, and use cutting‑edge ML research to transform how users interact with Samaya in their daily workflows. You'll drive impact across the entire ML lifecycle: from problem formulation and system analysis to data collection, benchmark development, model training, and production deployment. You’ll also have opportunities to publish your work and deliver impact to the ML community. Your expertise will advance our capabilities in these critical technical domains: Retrieval, ranking and RAG LLM post‑training and reinforcement learning AI agents for knowledge workflows Your work has the potential to transform the following key Samaya products and deliver impacts to tens of thousands of professional users: Instant QA: Our custom‑built Question Answer system using state of the art in‑house models, seamlessly trained to work together to enable instant expert intelligence. Agents: You will enable expert‑level agentic workflows to automate comprehensive knowledge work and enable AI tools that work with experts to gain new insights. Formulate an ML problem from product requirements. Analyze existing ML systems for their limitations, and propose and validate novel methodologies to improve upon existing systems. Create and productionize cutting‑edge research prototypes for knowledge work at scale. Build novel ML evaluation datasets that serve as crucial criteria for production feature rollouts. [Optionally] Mentor ML interns and publish your research findings with the community. Experience Required PhD or Master’s degree in Computer Science, Machine Learning, NLP, or a related field. Strong background in deep learning, large language models, and NLP techniques. A strong track record of first‑author publications in top AI/NLP conferences (e.g., NeurIPS, ICML, ACL, EMNLP). Proficiency in Python and deep learning frameworks such as PyTorch or Transformers, and strong coding skills. Preferred 2+ years of experience in an industry applied ML research environment Familiarity with retrieval‑augmented generation, reasoning, LLM training and reinforcement learning techniques. Compensation The cash compensation range for this role is $190,000 - $275,000. Final offer amounts are determined by multiple factors, including experience and expertise, and may vary from the amounts listed above. In addition to the base salary, we may consider equity as part of our total compensation package. Health: Access comprehensive health insurance, including medical, dental, vision, flexible spending account (FSA), and short‑term disability. Wealth: Support for your long‑term financial wellbeing with a 401(k) and pre‑tax benefits (e.g. commuting). Rest: Enjoy flexibility to rest and recharge as needed, with unlimited PTO (Paid Time Off). Flexibility: Work flexibly with a hybrid setup - typically team members spend a minimum of three days in the office per week. Travel: Grow and connect with a travel budget that encourages conference attendance, customer visits, and team gatherings. Equipment: Create your ideal workspace with an office Equipment allowance to set up what works best for you. Inclusive Hiring Interview Accommodations: We are committed to ensuring an equitable selection process for everyone and welcome applicants from varied backgrounds to enrich our team. If you require accommodations or adjustments during our recruitment process, please inform us. Equal Opportunity Employer: We do not discriminate on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non‑merit factor. Visa Sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. If we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. About Samaya Samaya is building the first AI agents designed specifically for expert knowledge work in financial services - one of the world’s largest and most information‑intensive industries. In today’s financial world, professionals face overwhelming volumes of fast‑moving, complex information. Traditional tools, and even general‑purpose AI, lack the accuracy, depth, and reliability needed for critical decisions. We believe AI should go beyond helpful suggestions, it should act as a true expert collaborator. Our mission is to supercharge financial research and decision‑making by empowering professionals to build their own teams of expert AI agents. These agents combine exceptional speed and precision: answering deep questions instantly, automating complex workflows, and delivering structured, predictive insights. Samaya’s platform combines cutting‑edge domain‑specialized AI models, a world‑class engineering and ML team, and a simple, intuitive interface designed for financial professionals. We’re growing quickly, our user base has scaled from hundreds to 10,000+, with partnerships spanning top financial institutions around the world, including Morgan Stanley, a top 5 hedge fund, a top 5 asset management firm, and more. We’re backed by $43.5M in Series A funding led by NEA, with investors including Eric Schmidt, Yann LeCun, Jeff Dean, Marty Chavez, and Mark Cuban. If you’re excited about building expert AI that transforms how knowledge work is done, and want to be part of a fast‑moving, supportive, and ambitious team - we’d love to hear from you. Put Users first. Our users rely on us to do their jobs. You keep their needs as your top priority. Win as a collective. We build strong bonds, help each other, and support learning and growth. Focus and iterate quickly. We prioritize important outcomes, take ownership, take fast action, and learn quickly. Innovate Relentlessly. We pursue novel insights and reimagine how things are done. Prioritize Outcomes over Egos. We focus on progress to our goals, ask tough questions, and embrace feedback. #J-18808-Ljbffr Alumni Ventures