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Senior Machine Learning Operations Engineer

Оценка ИИ

Отличная вакансия в стабильной логистической компании с современным стеком технологий и четкими перспективами роста. Привлекательный пакет бенефитов и работа в новом офисе в Гвадалахаре.


Вакансия из Quick Offer Global, списка международных компаний
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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует глубоких знаний как в программной инженерии (Python, распределенные системы), так и в специфике ML (модели, инференс). Высокий уровень ответственности за архитектуру платформы и наставничество делает позицию сложной.

Анализ зарплаты

Медиана85 000 $
Рынок65 000 $ – 110 000 $
Оценка ИИ

Зарплата для Senior MLOps ролей в Гвадалахаре обычно выше среднего по рынку ИТ в Мексике из-за дефицита специалистов такого уровня. Указанные рыночные оценки отражают уровень компенсации в международных технологических хабах.

Сопроводительное письмо

I am writing to express my strong interest in the Senior Machine Learning Operations Engineer position at Arrive Logistics. With over 5 years of experience in building scalable backend services and optimizing ML model serving, I am confident in my ability to lead your ML platform strategy. My background in Python, Kubernetes, and distributed systems aligns perfectly with your mission to build high-impact, profit-maximizing ML services.

In my previous roles, I have successfully designed and maintained complex ML infrastructures and mentored engineering teams to achieve technical excellence. I am particularly impressed by Arrive's commitment to a collaborative, in-person culture and your use of modern tools like Snowflake and Chalk. I am eager to bring my expertise in system design and event-driven architectures to your Guadalajara team and help drive the organization's engineering standards forward.

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Составьте идеальное письмо к вакансии с ИИ-агентом

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Откликнитесь в arrivelogistics уже сейчас

Присоединяйтесь к Arrive Logistics в Гвадалахаре и станьте лидером в создании передовых MLOps решений для логистики!

Описание вакансии

Who We Are

Arrive Logistics is a leading transportation and technology company in North America, with plans to continue to significantly grow year over year. Our success is a testament to our remarkable team and what we are building together. We’re committed to providing employees with a meaningful work experience and have established an award-winning culture that supports personal and career development in a fun, casual, and collaborative environment. There has never been a more exciting time to get on board, so read on to learn more and apply today!

Who We Want

As a Senior Machine Learning Operations Engineer at Arrive, you will serve as a key technical leader, responsible for defining, advancing and executing our overall ML platform strategy. This role also requires driving, contributing to, and maintaining the quality and functionality of crucial roadmap projects. These initiatives may vary from serving models scalably to building ML-powered services focused on maximizing profit.

What You'll Do

  • Design, build, and maintain scalable ML systems and infrastructure using Python, Postgres, and Elasticsearch.
  • Lead sprints, conduct rigorous code reviews, and set the "gold standard" for ML engineering practices across the organization.
  • Actively mentor junior and mid-level engineers, fostering a culture of technical excellence and professional growth.
  • Partner closely with other Machine Learning Engineers, Product Managers, Data Scientists, Data Engineers, and Product Engineers to ensure the successful delivery of strategic and roadmap initiatives
  • Independently and with relatively little oversight, own systems throughout the software development lifecycle, from design to development, deployment and monitoring.
  • Maintain and improve performance of existing data systems and processes while balancing maintainability, observability and readability.
  • Demonstrate a deep sense of ownership by developing a thorough understanding of a domain. At the same time, you must be able to explain the behavior of and contribute to code bases that may be outside your domain.
  • Proactively propose solutions to gaps or risks in process, technology, software design and architecture
  • Provide rigorous and detailed code reviews that uphold team standards, testing and software design best practices
  • Foster a culture of constant improvement and growth, engineering excellence, humility, positivity and curiosity. Take a lead role in making our two days in the office productive and engaging, fostering face-to-face mentorship and collaborative whiteboarding sessions.
  • In partnership with other leaders, establish best practices across the organization and drive the organization’s standards within the team, leading by example.

Qualifications

  • Bachelor’s degree in Computer Science, Engineering, or a related field or equivalent professional experience.
  • 5+ years of experience with ML ops, model serving and optimization. Experience with Chalk and Snowflake is a plus.
  • 5+ years of experience with Python, object oriented programming and building highly scalable backend services.
  • Expertise in frameworks like Sklearn, Pandas, Numpy. Bonus points if well versed in Huggingface, Tensorflow, Pytorch, Langchain and Langsmith.
  • 3+ years of experience with relational databases
  • 2+ years in a lead or senior-level capacity
  • 2+ years of experience designing maintainable and scalable systems
  • Proven expertise in system design with a focus on distributed systems and event-driven architectures
  • Experience developing cloud-native dockerized applications in Kubernetes
  • Experience working with online experimentation and platforms like Statsig
  • Understanding of both traditional machine learning and deep neural networks
  • Strong communication skills with the ability to articulate, diagram and document complex ML or engineering concepts.
  • Strong analytical, problem-solving, decision-making, and interpersonal skills.
  • Strong project management and organizational skills with experience identifying project milestones to ensure timely project delivery.
  • You are a self-starter who can deliver projects independently, yet you also thrive in collaborative environments. You recognize the value of diverse perspectives in developing optimal solutions and consistently demonstrate a willingness to support colleagues as a strong team player.
  • You approach software engineering as a craft, balancing the pursuit of clean, maintainable code with the demands of a fast-moving, dynamic business environment. You collaborate effectively with product managers and leadership to choose development paths that minimize technical debt while ensuring the timely delivery of high-quality products. While you have a strong drive for innovation, you also recognize the critical need to stabilize and harden existing products and services.
  • You find genuine joy in helping others level up their skills and navigate their career paths. You view peer reviews as a powerful tool for technical mentorship and can provide feedback in a constructive manner.
  • You are able to translate ambiguous and amorphous ideas or problems into concrete projects or initiatives while getting buy-in from engineering, data science, data engineering or product management partners.
  • You believe that while remote work is functional, in-person collaboration is where the "magic" happens. You are excited to help shape the energy of our physical workspace.
  • You take initiative to go beyond current responsibilities and actively seek new challenges.
  • You are passionate about building high impact ML and data driven products.

The Perks of Working With Us

  • Take advantage of our benefits including monthly grocery vouchers, vacation days, savings fund, medical insurance (including dental and vision plans) and more.
  • Leave the suit and tie at home; our dress code is casual.
  • Enjoy office wide engagement activities, team events, happy hours and more!
  • Work in our new Guadalajara office located in Torre 1500 (Av. Americas 1254) within the plaza, you'll find cafes and a wide variety of local restaurants.
  • Start your morning with free coffee!
  • Maximize your wellness with free counseling sessions through our Employee Assistance Program
  • Get paid to work with your friends through our Referral Program!

Your Arrive Experience

Our award-winning company culture is designed with you in mind. We are committed to supporting your personal and professional growth and making Arrive a place we all love to work.

*Notice:*

To ensure a safe and transparent interview process, we want to note that Arrive Logistics adheres to strict recruitment practices. Candidates undergo an interview process, and Arrive Logistics does not provide unsolicited job offers. If you have concerns about receiving a fraudulent offer, please contact talentacquisition@arrivelogistics.com for verification.

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Создайте идеальное резюме с помощью ИИ-агента

Создайте идеальное резюме с помощью ИИ-агента

Навыки

  • Python
  • NumPy
  • Pandas
  • PyTorch
  • Kubernetes
  • PostgreSQL
  • Scikit-learn
  • Docker
  • Snowflake
  • Distributed Systems
  • TensorFlow
  • Event-Driven Architecture
  • ElasticSearch
  • LangChain
  • Hugging Face
  • Chalk

Возможные вопросы на собеседовании

Проверка опыта проектирования масштабируемых систем инференса.

Как бы вы спроектировали систему для обслуживания ML-моделей с низкой задержкой при миллионах запросов в день?

Оценка навыков работы с современным стеком MLOps.

Опишите ваш опыт работы с Kubernetes и Docker для развертывания ML-сервисов. С какими основными проблемами вы сталкивались?

Проверка понимания жизненного цикла данных и моделей.

Как вы организуете мониторинг производительности моделей в продакшене и процесс автоматического переобучения?

Оценка лидерских качеств и умения проводить код-ревью.

Каковы ваши основные критерии при проведении код-ревью для ML-проектов, чтобы обеспечить поддерживаемость и чистоту кода?

Проверка умения работать с данными в реальном времени.

Расскажите о вашем опыте работы с событийными архитектурами (event-driven) в контексте машинного обучения.

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