Senior Data Scientist at Darrow

Tel-Aviv, Tel-Aviv District, Israel -

Full Time

Start Date

Immediate

Expiry Date

21 Feb, 26

Salary

0.0

Posted On

23 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Applied AI Research, Large Language Models, Machine Learning, Deep Learning, Python, TensorFlow, PyTorch, NLP, Model Compression, Knowledge Distillation, Retrieval-Augmented Generation, Collaboration, Problem Solving, Communication, Mentoring, Innovation

Industry

technology;Information and Internet

Description

About Darrow Darrow is on a mission to pursue frictionless justice -using data and AI to uncover large-scale harms and bring justice to the people. We’re a fast-growing startup of more than 150 team members based in Tel Aviv and New York, backed by world-class investors including Georgian, F2 Venture Capital, Entree Capital, NFX, and Y Combinator. At Darrow, we build products that turn data into justice. Our platform uncovers legal violations -like environmental crimes, financial fraud, and privacy breaches—and helps bring legal action to scale. The result? A justice system that works better, faster, and more fairly. Our Research team is growing, and we’re looking for an Applied Researcher to help us push the boundaries of large language models (LLMs) and applied machine learning in production. About the Role As an Applied Researcher at Darrow, you will play a central role in advancing our AI capabilities -fine-tuning and optimizing large language models to extract legal insights and power intelligent decision-making at scale. You’ll explore new model architectures, training paradigms, and evaluation methods to push research from experimentation to impactful, production-ready innovation. You’ll collaborate closely with data scientists, engineers, and domain experts to design and validate research prototypes, integrating cutting-edge methods such as model distillation, retrieval-augmented generation (RAG), and knowledge-graph–based reasoning. Responsibilities: Design and evaluate new model architectures, training objectives, and loss functions that enhance generalization and domain adaptation. Research and innovate in areas such as model compression, knowledge distillation, and retrieval-augmented generation (RAG) to improve inference efficiency and interpretability. Publish and present innovative findings internally and externally to advance the organization’s leadership in applied AI research. Collaborate cross-functionally with engineering, product, and data science teams to transition research prototypes into scalable production systems Drive measurable impact by translating research innovations into deployable solutions that improve model performance, scalability, and user outcomes. Contribute to the research community through publications, open-source contributions, or collaborations, showcasing thought leadership in LLM fine-tuning and applied AI innovation. Responsibilities null Requirements M.Sc. in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field. 5+ years of experience in applied AI research. Strong programming skills, particularly in Python and ML frameworks (e.g., TensorFlow, PyTorch). Solid understanding of NLP. Experience with modern Large Language Models (LLM) and generative models. Proven expertise in designing, implementing, and evaluating deep learning models in a production environment. Excellent communication, mentoring, and collaboration skills. A strong problem-solving mentality and a proactive demeanor, driven by the ambition to deliver solutions with real-world impact Advantages: Prior experience leading or working within cross-functional teams that include data scientists, operations research specialists, and software engineers. Passion for learning and stay informed with State of the Art progress

Responsibilities

As an Applied Researcher, you will advance AI capabilities by fine-tuning large language models to extract legal insights. You will collaborate with cross-functional teams to transition research prototypes into scalable production systems.