Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• We are seeking a Data Scientist to become a part of our Data Sciences and ML Engineering team. In this role, you will be responsible for constructing, deploying, and enhancing the models and LLM-powered systems that are fundamental to our security products.

• This position is hands-on and part of a small, dedicated team. You will have significant ownership over the models and pipelines you create, collaborate closely with engineering and product teams, and have the opportunity to delve deeply into challenging problems.

• Your responsibilities will encompass several areas:

• Model development and research. You will be creating classifiers, detectors, and scoring models on complex, high-stakes security data. This includes designing experiments, assessing trade-offs, and iterating on architectures beyond just hyperparameters.

• LLM agent systems. You will influence the prompts, context, tool-use patterns, and supporting content that drive our LLM agents.

• Production delivery. You will deploy models that handle real traffic, monitor their performance, and work on continuous improvements over time.

• Evaluation and iteration. You will develop the evaluation harnesses and feedback loops that inform us whether a change genuinely represents an improvement — often the most challenging aspect of the work. Our models enhance customer experience only when our evaluations highlight what truly matters.

⛳️ Requirements

• Production experience is a key requirement. We expect around 3–4+ years of experience in delivering models to production environments where they have been required to perform, be maintained, and evolve. This background typically lays the foundation for success in this role.

• Strong understanding of ML fundamentals. You possess knowledge of model architectures and can reason about why a particular approach is suitable or not for a given problem. You have moved beyond treating models as black boxes and beyond tuning that focuses solely on sample weights and decision thresholds.

• Openness to experimentation. You are comfortable exploring genuinely novel approaches when standard methods are insufficient, and you can distinguish between promising and fragile results.

• Solid engineering instincts. Your code is clear, maintainable, and trustworthy for your teammates in a production setting. You consider reproducibility, testing, and handoff — not just whether the code works on your laptop.

• Practical experience with LLMs. You have engaged with LLM-based systems in a real-world context — including prompting, context design, tool use, evaluation, or fine-tuning — and your opinions are informed by practical experience of shipping projects.

• Ability to navigate ambiguity. Security challenges seldom present with clean labels or tidy data. You can define problems, scope them, and make progress without a fully defined path. You will help clarify ambiguities and reason through how to advance even when consensus is lacking.

• An advanced degree (MS or PhD) in a technical field. This does not need to be specifically in data science or ML — strong backgrounds in computer science, statistics, physics, mathematics, engineering, and related disciplines are all welcomed. Your hands-on experience is what holds the most value.

🏝️ Benefits

• Fully Remote: Our team operates completely remotely on a global scale. Although we are distributed, we intentionally come together a couple of times each year. We provide a generous stipend for your home office setup, annual upgrades to ensure a comfortable workspace, and a monthly stipend for internet and phone expenses.

• Comprehensive Health & Wellness Benefits: Our healthcare benefits exceed those of typical startups. With five fully subsidized options provided by HiddenLayer, we offer a variety of plans to meet individual needs. Our offerings also include vision, dental, and 401k options.

• Flexible Time Off: We provide unlimited and flexible time off for all salaried employees, alongside 15 paid company holidays.

• Commitment to Learning and Development: We encourage personal growth and education through a dedicated L&D fund that can be utilized for training, conferences, certifications, and industry events.

• Diversity, Equity, and Inclusion: We are dedicated to assembling a diverse team with individuals from a variety of backgrounds, experiences, abilities, and perspectives, and we take pride in being an equal opportunity employer.