- Страна
- США
Откликайтесь
на вакансии с ИИ

Data/ML Infrastructure Engineer
Отличная вакансия для инженеров, желающих работать на стыке AI и реального мира (космос, дроны). Предлагается полный пакет бенефитов (100% страховка) и опционы на ранней стадии, что дает высокий потенциал роста, несмотря на отсутствие указанной зарплаты.
Сложность вакансии
Высокая сложность обусловлена необходимостью глубоких знаний как в Data Engineering, так и в ML Infrastructure, а также строгими требованиями ITAR (гражданство или грин-карта США). Работа с геопространственными данными и сенсорами требует специфического опыта в оптимизации производительности и стоимости облачных вычислений.
Анализ зарплаты
В Сан-Франциско для позиций уровня Senior/Staff в области ML Infrastructure рыночные зарплаты начинаются от $180,000 и могут достигать $250,000+ без учета опционов. Данная вакансия, вероятно, находится в этом диапазоне, учитывая сложность задач и локацию.
Сопроводительное письмо
I am writing to express my strong interest in the Data/ML Infrastructure Engineer position at Matter Intelligence. With a solid background in building production-grade distributed systems and a deep understanding of the intersection between data and ML platforms, I am excited about the opportunity to help scale your infrastructure for drone and orbital sensing data.
In my previous experience, I have focused on building reliable data pipelines and ML platform primitives using AWS, Kubernetes, and Terraform. I share your commitment to reproducibility and observability, and I am particularly drawn to Matter's mission of turning complex sensor data into actionable insights. I am confident that my skills in Python, SQL, and infrastructure automation will allow me to contribute immediately to your research and product engineering workflows.
Составьте идеальное письмо к вакансии с ИИ-агентом

Откликнитесь в matter-intelligence уже сейчас
Присоединяйтесь к команде Matter Intelligence и создавайте инфраструктуру будущего для обработки данных с дронов и спутников!
Описание вакансии
About the Role
We are seeking a Data Infrastructure Engineer to build and operate the infrastructure that turns drone, aerial, and orbital sensing data into production datasets, models, and customer-facing insights. This role spans ingestion, processing, storage, compute, and serving, with a strong emphasis on reliability, observability, performance, and cost.
You will work closely with research and product engineering to shorten iteration cycles, improve reproducibility, and raise the quality bar for production systems. You will define clear interfaces and operational standards that keep the platform trustworthy as data volume, model complexity, and product usage scale.
What You’ll Do
- Design, build, and operate scalable data and ML infrastructure on AWS, including workloads running on Kubernetes
- Build and maintain systems for ingestion, processing, storage, and serving, with strong guarantees around data quality, correctness, and operational safety
- Partner closely with research to support perception model training and evaluation workflows, enabling faster experimentation and more reproducible iteration
- Build platform primitives for observability, data versioning, lineage, evaluation, reproducibility, and operational excellence
- Partner with product engineering to ensure data- and model-derived insights are accessible through reliable, low-latency serving and retrieval interfaces
- Design systems that enable efficient access patterns for customer-facing products, including search, indexing, and large-scale querying
- Identify and address bottlenecks in throughput, cost, and operational complexity as the platform scales
What We’re Looking For
You have strong software engineering fundamentals and have built production systems where reliability, cost, and performance matter. You can reason clearly about distributed systems tradeoffs, and you have experience designing data-intensive infrastructure that other engineers depend on.
You are comfortable working across data platform and ML platform concerns, and you understand how tightly coupled they become in production. You care about reproducibility, debuggability, and developer experience because you have seen how quickly they become bottlenecks.
You work effectively across research and product teams. You can translate ambiguous needs into clear interfaces and systems, and you can drive work from design through production while maintaining a high quality bar.
A few things we expect in this role:
- Meaningful experience building production data infrastructure, ML infrastructure, or distributed systems
- Strong programming skills in Python and SQL, with the judgment to choose the right abstractions and interfaces for production systems
- Experience building and operating systems on AWS
- Familiarity with modern infrastructure and platform tooling, including Kubernetes, Docker, and Terraform
- Experience working with production storage and serving systems such as Postgres and Redis
- Familiarity with data and ML workflow tooling such as Metaflow
- Strong instincts for observability, testing, and operational excellence
Nice to Have
- Experience supporting ML training, evaluation, batch inference, or model deployment in production
- Familiarity with modern large-scale data patterns and tooling, including streaming, backfills, partitioning strategy, and schema evolution
- Experience building internal platform primitives such as data versioning and lineage, dataset curation, experiment tracking, or tooling for reproducible workflows
- Exposure to perception, multimodal, or geospatial systems, especially where data originates from real sensors and is used in real products
Location
This is a full-time role based in San Francisco, CA.
ITAR Requirements
To comply with U.S. export regulations, applicants must be one of the following:
- A U.S. citizen or national
- A lawful permanent resident (green card holder)
- Eligible to obtain required authorizations from the U.S. Department of State
Employee Offerings & Benefits
At Matter, we believe in rewarding high performance and providing the support you need to thrive. Our compensation and benefits package includes:
- Competitive compensation based on experience
- Early-stage equity package
- 100% employer-paid health, dental, and vision coverage
- Opportunity to work on novel sensing, data, and AI systems with real-world deployment paths across drone, aerial, and orbital platforms
Who You Are
You are a strong engineer who likes building reliable systems that other teams can trust. You care about infrastructure quality, operational rigor, and clear interfaces. You are energized by working close to the data, close to the models, and close to the product.
Создайте идеальное резюме с помощью ИИ-агента

Навыки
- Python
- SQL
- AWS
- Kubernetes
- Docker
- Terraform
- PostgreSQL
- Redis
- Metaflow
- Distributed Systems
- ML Infrastructure
- Data Infrastructure
Возможные вопросы на собеседовании
Проверка опыта работы с основным стеком и понимания контейнеризации в облаке.
Расскажите о вашем опыте развертывания и масштабирования ML-нагрузок в Kubernetes на базе AWS. С какими основными трудностями вы сталкивались?
Оценка навыков проектирования систем и понимания жизненного цикла данных.
Как бы вы спроектировали систему версионирования данных и обеспечения их происхождения (lineage) для мультимодальных сенсорных данных?
Проверка умения оптимизировать затраты и производительность.
Какие стратегии вы используете для оптимизации стоимости хранения и обработки огромных объемов данных в S3 и Postgres при работе с высокочастотными сенсорами?
Оценка опыта работы с инструментами оркестрации.
Был ли у вас опыт работы с Metaflow или аналогичными инструментами? Как вы обеспечиваете воспроизводимость экспериментов для команды Research?
Проверка навыков обеспечения надежности.
Опишите ваш подход к мониторингу и алертингу для пайплайнов обработки данных в реальном времени. Какие метрики вы считаете критическими?
Похожие вакансии
MLOps Engineer (ML pipelines / Kubernetes / Airflow)
Senior Data инженер
Senior MLOps Engineer (Platform Development / LLMOps)
Data Engineer / SAP HANA Developer (Senior)
Data Scientist в RecSys
Data Engineering Team Lead (команда Clickhouse)
1000+ офферов получено
Устали искать работу? Мы найдём её за вас
Quick Offer улучшит ваше резюме, подберёт лучшие вакансии и откликнется за вас. Результат — в 3 раза больше приглашений на собеседования и никакой рутины!
- Страна
- США