- Страна
- США
- Зарплата
- 230 000 $ – 322 000 $
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Staff Software Engineer, ML Search
Исключительная вакансия в топовой технологической компании с прозрачной и высокой оплатой. Полная удаленка, работа с уникальными данными и масштабными задачами делают это предложение одним из лучших на рынке.
Сложность вакансии
Роль уровня Staff требует не только глубоких технических знаний в ML и поиске, но и подтвержденного опыта руководства сложными проектами. Ожидается свободное владение стеком Big Data и опыт работы с системами сверхвысокой нагрузки.
Анализ зарплаты
Предлагаемая зарплата ($230k - $322k) находится на верхнем уровне рыночных ожиданий для Staff-позиций в США. С учетом бонусов и опционов (RSU), совокупный доход значительно превышает средние показатели по индустрии.
Сопроводительное письмо
I am writing to express my strong interest in the Staff Software Engineer, ML Search position at Reddit. With over 8 years of experience in building large-scale search and recommendation systems, I have a proven track record of designing robust infrastructure that powers real-time ranking and retrieval. My background in optimizing low-latency model-serving APIs and managing complex data pipelines aligns perfectly with the goals of the Search & Recommendation Relevance team.
Throughout my career, I have successfully navigated the challenges of scaling ML systems for hundreds of millions of users. I am particularly drawn to Reddit's unique challenge of surfacing relevant content from the world's largest corpus of human conversation. My expertise in Python, Go, and big data technologies like Airflow and Kubernetes will allow me to contribute immediately to your infrastructure and help other MLEs iterate faster on their models.
I am excited about the opportunity to bring my technical leadership and passion for search relevance to Reddit. Thank you for considering my application. I look forward to the possibility of discussing how my experience can help drive discovery across Reddit’s diverse communities.
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Откликнитесь в reddit уже сейчас
Присоединяйтесь к команде Reddit и создавайте поисковые системы нового поколения для миллионов пользователей по всему миру!
Описание вакансии
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 121 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.
Location:This role iscompletely remote-friendly. If you happen to live close to one of our physical office locations, our doors are open for you to come into the office as often as you'd like.
Team Description:The Search & Recommendation Relevance team focuses on delivering the most relevant results when users search for anything on Reddit. Our systems and algorithms operate on the world's largest corpus of human conversation, showcasing the best answers and diverse opinions from all across Reddit on any topics - whether it's recommendations for the best hiking trail, travel advice, or reviews of the next product or restaurant. To achieve this, our Search Recommendation systems need to be built for maintainability, scalability, and low latency in mind.
As a Staff Software Engineer, ML Search, you’ll build backend and pipeline systems that turn models into real search experiences for 110M+ daily users, owning data flows, ranking and retrieval services, and low-latency model-serving APIs. You’ll integrate models into production through robust interfaces and DAGs, enabling fast iteration and powering discovery across the internet’s largest community platform.
Responsibilities:
- Own pipelines and DAGs that move data, features, embeddings, and models through the ML lifecycle
- Design/maintain ranking and retrieval services that run models in real-time
- Build scalable model-serving APIs, ensuring reliability, efficiency, and performance
- Create reusable infrastructure that other MLEs depend on to train, deploy, and iterate on models
- Ensure pipelines and systems support high scale, low latency, and operational excellence
- Enable modeling with better systems, features, and deployment pathways
Qualifications:
- 8+ years of industry experience with a focus on search and recommendation systems.
- 6+ years of experience in designing, building and iterating large-scale search relevance and infrastructure systems, handling end-to-end system development.
- Proven track record in delivering large and complex systems with big business impacts.
- Knowledge and experience working with search systems (e.g. Lucene, Solr, ElasticSearch, Opensearch etc.).
- Demonstrated expertise at cross-functional collaboration - successfully shipped several large-scale projects with complex dependencies across teams.
- Proficient in object-oriented programming (Python, Golang).
- Experience in API design and integration with GraphQL, REST, HTTP, Thrift or gRPC.
- Experience of developing applications using large-scale data stack - e.g. Kubeflow, Airflow, BigQuery, Kafka, Kubernetes, Redis etc.
Benefits:
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
#LI-DB1 #LI-Remote
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.
To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
The base salary range for this position is:
$230,000—$322,000 USD
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
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Навыки
- Python
- Go
- Machine Learning
- Search Systems
- Lucene
- Solr
- ElasticSearch
- OpenSearch
- GraphQL
- REST
- gRPC
- Kubeflow
- Airflow
- BigQuery
- Kafka
- Kubernetes
- Redis
- Distributed Systems
Возможные вопросы на собеседовании
Для позиции Staff важно понимать, как кандидат проектирует системы, способные выдерживать нагрузку в 100М+ пользователей.
Опишите архитектуру системы ранжирования в реальном времени, которую вы проектировали: как вы обеспечили низкую задержку (low latency) при использовании тяжелых ML-моделей?
Reddit использует огромные объемы данных; важно уметь эффективно ими управлять.
Как бы вы организовали жизненный цикл эмбеддингов в масштабах Reddit, чтобы обеспечить консистентность между обучением и инференсом?
Вакансия требует опыта работы с Lucene/ElasticSearch.
В каких случаях вы бы предпочли кастомное решение для векторного поиска вместо стандартного Elasticsearch/OpenSearch?
Staff-инженер должен уметь работать с кросс-функциональными зависимостями.
Расскажите о случае, когда вам пришлось внедрять критическое изменение в инфраструктуру, которое затрагивало несколько команд. Как вы управляли рисками?
Вакансия упоминает Kubeflow и Airflow.
Как вы подходите к обеспечению отказоустойчивости и мониторингу сложных ML-пайплайнов (DAGs) в продакшене?
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- Страна
- США
- Зарплата
- 230 000 $ – 322 000 $