Delivery Hero·26 авг.
Senior Machine Learning Engineer
Ориентир по рынку≈ 436 000 – 487 000 ₽наша приблизительная оценка по 14 вакансиям этой роли и грейда, у работодателя вилка не указана
≈ 5,4 тыс.–6 тыс. $
ОфисSeniorПолная занятость
≈ 436 000 – 487 000 ₽наша приблизительная оценка
Стоит ли откликаться
Стоит откликнуться, но спросите про деньги
Сумму в объявлении не указали. Сколько платят за похожую работу, видно в разборе. Правда, вакансия открыта уже давно.
2 из 4 в норме
Открыта долго: как понять до отклика, ищут ли ещё
Деньги
Зарплату в объявлении не раскрыли. Ориентир на созвон: столько платят в 14 похожих вакансиях Data Scientist уровня Senior.
Живость
Висит 60 дней. Источник её не снимает, но так долго открытые позиции бывают трудными для найма или набором в резерв.
- Зарплата не указана
Описание
Расписано подробно: обязанностей 18, требований 4. Картина ясна до первого созвона.
Что требуют
ОбязательноMLMLOpsPython
ПлюсомAirflowAWSGCPCI/CDTerraformDocker
Надбавка к зарплате на этом уровне: Python +14%, CI/CD +7%, Docker +6%.
Полный разбор в Pro
Это короткий разбор. В Pro полный: под эту вакансию и ваше резюме
Сколько просить
Не продешевите: сумма под ваше резюме, нижняя граница и готовые фразы для торга
Ваше резюме против требований
Пройдёт ли ваше резюме фильтр: что совпало с требованиями и что дописать до отклика
Спросить у работодателя
10 вопросов именно к этой вакансии: что спросить на первом созвоне
Когда откликаться
Стоит ли спешить: за сколько дней Delivery Hero обычно закрывает вакансии
30 дней Pro: полный разбор каждой вакансииЧто ещё входит в Pro
Вакансия на английскомПереведёт заголовок и описание вакансии на русский
Наша компания
As the world’s pioneering local delivery platform, our mission is to deliver an amazing experience, fast, easy, and to your door. We operate in around 65 countries worldwide, powered by tech, designed by people. As one of Europe’s largest tech platforms, headquartered in Berlin, Germany, Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index. We push hard, learn quickly and stay human along the way. It’s this wonderful mix of high performance and real community that makes Delivery Hero a place where ambition and belonging grow side by side. If you’re curious, collaborative and ready to dive deep into meaningful work, you’ll fit right in.
Чем предстоит заниматься
RELOCATION TO GERMANY | DELIVERY HERO
We are on the lookout for a Senior Machine Learning Engineer to join the Logistics Optimization team on our journey to always deliver amazing experiences
The Optimization Tribe's purpose is to maximize Delivery Hero's logistics performance. We achieve this by owning and continuously improving the sophisticated algorithm that solves the real-time vehicle routing problem, assigning orders efficiently every second across the world. This directly impacts DH's core efficiency and customer satisfaction KPIs, influencing decisions for stakeholders from Operations to Product
As an ML Engineer, your value lies in tackling the problems at scale head-on and building ML models and products which shape the algorithm's logic and decisions to meet our long-term goals of best-in-class efficiency and service, making a tangible impact across the Delivery Hero network. Are you ready to take your Machine Learning Engineering and Data Science skills to the next level and make a tangible impact on millions of users worldwide?
In this role you will
Build and Maintain: Design, build and maintain scalable ML models services, optimizing for performance and efficiency
Design Robust Architecture: Build the infrastructure that powers critical model inputs fed every minute to the dispatch algorithm which shapes experiences for millions of customers across the globe, every single day
Collaborate and Optimize: Work closely with data scientists and engineers to understand their product needs and build scalable solutions
Develop Tooling: Build and enhance ML engineering tooling for Model Development, Monitoring, Serving, and Experimentation
Leverage Cloud: Utilize DH cloud infrastructure built with modern technologies on popular cloud platforms to build highly available systems for multiple teams
Innovate and Suggest: Proactively suggest how the team can leverage new technologies and architectures to support new use cases
What you need to be successful
ML Engineering Experience: Prior experience (Ideally 4+ years) in ML engineering or MLOps and familiar with the ML engineering ecosystem tools used for Model serving, training, experimentation, and feature engineering. Have experience building infrastructure around machine learning pipelines leveraging modern tools with hands-on experience in modern programming languages such as Python
ML and DS Experience: You have significant experience (ideally 3+ years) designing and implementing diverse machine learning models (e.g., regression, classification, tree-based ensembles) to solve real-world business problems, backed by a strong theoretical foundation in statistics and probability
Application Development: Experience building new applications from scratch along with experience building quick proof of concepts (PoCs) for solving system design challenges using open-source tools
Technical Evaluation: Experience in tech explorations to evaluate technologies for business problems and proposing solutions based on comprehensive pros and cons analysis
System Analysis: Experience in deep-diving into existing systems for investigations and improvements
Communication Skills: Fluency in English. Clarity in communication, both written and verbal
Наши требования
Experience with ML tools like Metaflow, Airflow, MLflow, Argo Workflows, and Cloud Notebooks, etc
Prior knowledge of public cloud platforms (AWS, Google Cloud or equivalent)
Experience with CI/CD pipelines and Infrastructure as Code (Terraform or equivalent)
Knowledge of containerization and orchestration tools like Docker, Kubernetes, and Helm
Мы предлагаем
Ensuring you and all our Heroes are looked after, happy, and healthy is always on the menu. Because if you’re in good shape, then we’re in good shape
Make the most of our hybrid working model ( join the team for face-to-face connection and collaboration in our beautiful Berlin campus 2 days a week
We offer 27 days holiday with an extra day on 2nd and 3rd year of service
We will support you in developing yourself and your career growth opportunities: 1.000 € Educational
