Team Lead NLP Engineer | LLM & AI Product

Привет! Мы – команда Machine Learning Technology Research and Development (MLTech), и мы приглашаем специалистов по Data Science решать с нами задачи на стыке машинного обучения и кибербезопасности: детектировать зловредные файлы, распознавать фишинговые веб-страницы и обнаруживать хакеров в корпоративных сетях.

Что предлагает наша команда:
 

·       мы помогаем друг другу расти и добиваться результатов, решая прикладные задачи;

·       у нас есть MLOps’ы, которые помогут не запутаться в инфраструктуре;

·       не боимся использовать новые технологии и пробовать новые идеи;

·       результаты твоей работы почувствуют на миллионах устройств по всему миру;

·       используем Spark-кластер и GPU-кластер, чтобы обрабатывать огромные коллекции файлов;

·       при желании о результатах работы можно рассказывать в статьях и на конференциях.

Ты подходишь нам, если:
 

·       имеешь опыт машинного обучения в индустрии;

·       готов глубоко погружаться в данные, анализировать модели и строить интерпретации, общаться с заказчиками и превращать их пожелания в гипотезы;

·       готов работать над разнообразными задачами, в которых нельзя просто `import ml`;

·       хочешь доводить проекты до прода и не боишься выходить за пределы jupyter-тетрадок;

·       понимаешь, зачем нужно observability для агентов и умеешь заставлять LLM сделать ровно то, что нужно;

·       любишь обсуждать идеи, свой код и чужой код с коллегами;

·       интересуешься безопасностью и не теряешься, услышав слова «полиморф» и «фишинг» (или хочешь во всем этом разобраться).
 

Хард-требования:

·       умеешь писать чистый и понятный код на современном Python;

·       хорошо ориентируешься в классическом ML и соответствующих библиотеках (scikit-learn, CatBoost);

·       имеешь опыт разработки систем на базе LLM: написание агентных систем, RAG-пайплайнов;

·       помнишь, что такое доверительный интервал;

·       умеешь писать несложные Docker-файлы (или готов научиться).

What's the opportunity? 

Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands.

We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test.

We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy.

What will I be doing? 

• Play an active role in hiring, mentoring and career development of other engineers
• Raise the bar for technical standards, performance, reliability, and operational excellence
• Identify areas where ML can create value for our customers
• Identify the right ML framing of product problems - Working with teammates and Product and Design stakeholders
• Conduct exploratory data analysis and research - Deeply understand the problem area
• Research and identify the right algorithms and tools - Being pragmatic, but innovating right to the cutting-edge when needed
• Perform offline evaluation to gather evidence an algorithm will work
• Work with engineers to bring prototypes to production
• Plan, measure & socialize learnings to inform iteration
• Partner deeply with the rest of team, and others, to build excellent ML products

What skills might I need? 

• 5-8 years applied ML experience
• Previous background in a senior/staff role (data science, software development or academic)
• Significant, demonstrated impact that your work has had on the product and/or the teams
• Strong programming skills
• Experience as the primary technical leader for a team
• Strong communication skills, both within engineering teams and across disciplines.
• Comfort with ambiguity
• Typically have advanced education in ML or related field (e.g. MSc)
• Scientific thinking skills

Bonus skills & attributes 

• Track record shipping ML products
• PhD or other experience in a research environment
• Deep experience in an applicable ML area - E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering
• Strong stats or math background
• Visualization, data skills, SQL, matplotlib, etc.

About the Team:

Netlify’s Data team helps the company understand and improve the full product-led growth journey, from activation and engagement through conversion, retention, and monetization. We partner closely with Product, Engineering, and Growth to uncover opportunities, evaluate investments, and understand what drives customer and business outcomes.

We’re hiring a Senior Staff Data Scientist to deepen how data shapes our product and growth strategy. You’ll develop an end-to-end understanding of the PLG journey, proactively identify opportunities, and turn complex data into hypotheses, experiments, and recommendations that influence where we invest and what we build. This is a highly autonomous role for someone who can move from identifying an important question to shaping the approach, defining success, and driving toward an answer.

What You'll Do:

• Own the analytical understanding of Netlify’s PLG performance across activation, engagement, conversion, monetization, and retention, identifying opportunities before they become requests
• Partner with Product and Engineering leadership to turn behavioral insights into product bets, defining what to test, how to measure it, and what the results mean
• Lead experimentation from hypothesis through decision, including study design, methodology, success metrics, guardrails, analysis, and recommendations
• Apply statistical rigor where it matters while recognizing when there is enough signal to make a decision and move forward, and help teams develop that same judgment
• Build scalable analytical systems like semantic models, trusted metrics, proactive monitoring, and AI-powered agents  that surface opportunities without waiting to be asked
• Use AI to investigate faster, automate recurring analytical work, and test more hypotheses without sacrificing the judgment that makes the output useful
• Identify gaps in measurement, event instrumentation, and metric definitions, and partner with Data and Product Engineering to close them
• Serve as a trusted analytical partner to PLG leadership, using evidence and product judgment to influence investment decisions and roadmap priorities
• Influence product strategy through evidence, product instincts, and a clear point of view, without relying on formal authority to do it

What You'll Bring:

• 8+ years of experience in product analytics, growth analytics, or data science, with a track record of high ownership and measurable impact on PLG or consumer product outcomes
• Deep understanding of product and growth dynamics across activation, engagement, conversion, monetization, and retention
• Demonstrated ability to turn behavioral data into product hypotheses and carry them from insight through experimentation and measured outcomes
• Deep experimentation expertise: study design, statistical reasoning, causal inference, and the judgment to know when an experiment has told you what you need to know
• Experience building analytical systems such as metrics layers, monitoring frameworks, or semantic models that teams can rely on over time
• An AI-native approach to analysis: you use AI tools actively to accelerate investigation, automate repetitive work, and surface patterns faster
• A track record of influencing senior stakeholders and product direction through analytical reasoning, clear recommendations, and sound judgment
• Comfort operating with significant autonomy in ambiguous problem spaces, including determining which questions are most important to answer
• Strong written and verbal communication skills in distributed environments, with the ability to make complex findings clear and recommendations actionable

This Role is a Great Fit If:

• You're energized by finding the opportunity before anyone thought to ask - proactive discovery is how you naturally work, not a mode you shift into
• You think like a product person who happens to be exceptionally rigorous with data, not a data person who occasionally weighs in on product
•  You thrive when the problem isn't handed to you - you'd rather define the question worth asking than answer the one that landed in your queue
• You get excited about building systems that keep working after you've moved on to the next problem
• You're comfortable making a call with imperfect information and can articulate clearly why you made it
• You enjoy being a thought partner to senior leaders - shaping how they think about investment and opportunity, not just supporting decisions already made
• You work well in a remote-first, async environment where written clarity and self-direction matter more than proximity
• You're drawn to roles where the measure of success is outcomes, decisions made, bets tested, metrics moved, not volume of output produced

Applying

Not sure you meet 100% of our qualifications? Please apply anyway!

When applying please include: 

A resume or short listing of your job history & skills (link to a LinkedIn profile would be fine). We appreciate a cover letter explaining why you would enjoy working in this role at Netlify to get to know you a bit better, though this is not required and will not impact your application. Our mission is to “build a better web” and that cannot be done without a diversity of skill sets, backgrounds and thoughts. 

Of everything we've ever built at Netlify, we are most proud of our team. Netlify is an Equal Opportunity Employer. We are devoted to building a team of people with diverse backgrounds and lifestyles. Driving equality empowers our team, enables us to innovate, and helps us maintain a more inclusive environment. We don’t discriminate against employees or applicants based on gender identity or expression, sexual orientation, religion, age, race, military/veteran status, citizenship, pregnancy status, or any other differences. If we can do anything to provide a better interview, i.e. accommodate a disability, then please let us know by emailing accommodations@netlify.com. 

About Netlify

Netlify is the most popular way to build, deploy, and scale modern web applications, empowering everyone from fast moving solo developers to enterprise teams. Millions of developers and organizations rely on Netlify as their platform of choice for composing web applications that are production ready, performant, and flexible. Now, as we embrace the next era of software development, we are embedding the same fluid, intuitive experience into the Agent Experience (AX), making it just as simple for intelligent agents to understand, interact with, and act on our platform as it is for developers. Whether your user is human or machine, Netlify ensures the path from idea to URL is seamless, fast, and deeply reliable.

We are a Series D company that has raised over $200M from investors such as Andreessen Horowitz, Kleiner Perkins, EQT, Bessemer, BOND, and Menlo Ventures. As a fully distributed company, we aim to create a company culture where the best idea can come from anywhere and strive to be thoughtful, compassionate, and collaborative in our work. If this sounds like something you’d like to be part of, we’re excited to connect with you!

At Netlify, we are committed to a compensation philosophy that prioritizes fairness and equity, positions our employee compensation competitively in the market, recognizes and rewards performance, and takes a comprehensive approach to our rewards package. We anchor our compensation philosophy on a market-based approach, therefore salary ranges may differ depending on the labor cost in a particular location. The salary provided is in addition to robust benefits and participation in Netlify’s equity plan. Our hiring range for this role is targeted at $204,000 - $275,000 for most US-based locations.  Candidates outside the US or in premium markets should consult with their Talent Acquisition partner regarding location-based ranges, as they may be higher or lower than the average US range listed. The starting pay will be determined based on multiple factors, including expertise and skills, market demands, experience, internal equity, and applicable geographic location. These compensation packages and ranges are subject to change and may be modified in the future.