Data Scientist

🕒 Abril 27

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HiddenLayer

SiteLinkedInTodas as Vagas

51 - 200 funcionários

Fundada em 2022

🤖 Inteligência Artificial

🔒 Cibersegurança

💳 Fintech

Artificial Intelligence • Cybersecurity • Fintech

HiddenLayer é a primeira plataforma de segurança dedicada à inteligência artificial, projetada para proteger modelos de IA contra ataques adversariais que podem ameaçar vantagens competitivas. Em parceria com a Microsoft Azure, a HiddenLayer oferece um conjunto de soluções que inclui detecção e resposta para IA, varredura de segurança e relatórios automatizados para proteger algoritmos de aprendizado de máquina sem precisar de acesso aos dados subjacentes. Fundada por profissionais com ampla experiência em IA e segurança, a HiddenLayer tem como objetivo fornecer uma forma direta e eficaz para que as empresas protejam seus ativos de IA.

Descrição

• You're looking for a Data Scientist to join our Data Sciences and ML Engineering team. You'll be building, shipping, and improving the models and LLM-powered systems that sit at the core of our security products. • This is a hands-on role on a small, focused team. You'll have real ownership over the models and pipelines you build, close collaboration with engineering and product, and the runway to go deep on the hard problems. • Your work will span a few areas: • Model development and research. Building classifiers, detectors, and scoring models on messy, high-stakes security data. Designing experiments, evaluating trade-offs, and iterating on architectures — not just hyperparameters. • LLM agent systems. Shaping the prompts, context, tool-use patterns, and supporting content that drive our LLM agents. • Production delivery. Shipping models behind real traffic, monitoring them, and improving them over time. • Evaluation and iteration. Building the evaluation harnesses and feedback loops that let us know whether a change is actually an improvement — often the hardest part of the work. Our models only improve for customers when our evaluations highlight what really matters.

🎯 Requisitos

• Production experience is the single most important thing. We'd like to see around 3–4+ years of experience delivering models into production environments where they've had to perform, be maintained, and evolve. That's the background that tends to set people up for success here. • Depth in ML fundamentals. You understand model architectures and can reason about why a given approach is or isn't a good fit for a problem. You've moved well past treating models as black boxes and past tuning that stops at sample weights and decision thresholds. • Willingness to experiment. You're comfortable trying genuinely novel approaches when the standard playbook runs out, and you can tell the difference between a promising result and a fragile one. • Strong engineering instincts. Your code is something teammates can read, extend, and trust in production. You think about reproducibility, testing, and handoff — not just whether something runs on your laptop. • Experience with LLMs in practice. You've worked with LLM-based systems in some real capacity — prompting, context design, tool use, evaluation, or fine-tuning — and have opinions shaped by actually shipping things. • Comfort with ambiguity. Security problems rarely come with clean labels or clean data. You're able to frame problems, scope them, and make progress without a fully paved path. You’ll help highlight ambiguity and reason about how to make progress even when humans don’t all agree on one single answer. • An advanced degree (MS or PhD) in a technical discipline. This doesn't have to be in data science or ML specifically — strong backgrounds in CS, statistics, physics, math, engineering, and related fields are all welcome. Your on-the-job experience is what matters the most.

🏖️ Benefícios

• Fully Remote: We are a completely remote global team. Though we’re distributed, we are intentional about getting the team together a couple of times a year. We offer a generous stipend for your home office setup, annual upgrades to ensure you have a comfortable workspace and a monthly stipend for internet/phone expenses. • Comprehensive Health & Wellness Benefits: Better than your average startup healthcare benefits. With five options to choose from, of which are fully subsidized by HiddenLayer, we offer a variety of options to fit each person’s needs. We also offer vision, dental, and 401k offerings. • Flexible Time Off: Enjoy unlimited and flexible time off for all salaried employees, in addition to 15 paid company holidays. • Commitment to Learning and Development: We support personal growth and education through a dedicated L&D fund that can be used for training, conferences, certifications and industry events. • Diversity, Equity, and Inclusion: We are committed to building a diverse team with individuals from various backgrounds, experiences, abilities, and perspectives, and we are proud to be an equal opportunity employer.