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bloomreach
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SeniorГибридПолная занятость

Senior AI/ML Engineer

Оценка ИИ

Отличная вакансия в известной продуктовой компании с сильной инженерной культурой. Привлекательный пакет бонусов (акции, бюджет на обучение, DisConnect дни) и работа с современным стеком технологий делают это предложение очень конкурентоспособным.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует глубоких знаний как в разработке ПО (Python, API, микросервисы), так и в машинном обучении (MLOps, TensorFlow, Spark). Высокая сложность обучена необходимостью работы с высоконагруженными системами и сложными пайплайнами данных в среде SaaS.

Анализ зарплаты

Медиана5 500 €
Рынок4 500 € – 7 000 €
Оценка ИИ

Предложенная зарплата от 4000 EUR гросс соответствует рыночному уровню для Senior-специалистов в Словакии и Чехии, однако для топовых экспертов в области AI/ML верхняя граница может быть выше. Дополнительные бонусы в виде опционов (RSU) значительно повышают общую ценность компенсации.

Сопроводительное письмо

I am writing to express my strong interest in the Senior AI/ML Engineer position at Bloomreach. With a solid background in Python engineering and a proven track record of deploying ML-powered features into production, I am excited about the opportunity to contribute to the Loomi AI engine. My experience aligns perfectly with your requirements for building scalable APIs, managing complex data pipelines with Spark and TensorFlow, and implementing MLOps best practices in a GCP environment.

Throughout my career, I have focused on bridging the gap between data science and production-ready software. I am particularly drawn to Bloomreach's mission of revolutionizing conversational shopping and autonomous marketing. I am confident that my technical expertise in designing high-performance serving endpoints and my passion for continuous discovery will allow me to make a significant impact on your engineering team and help deliver exceptional value to your 1,400+ global brands.

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Откликнитесь в bloomreach уже сейчас

Присоединяйтесь к Bloomreach, чтобы создавать будущее персонализированной коммерции с помощью передовых технологий Loomi AI!

Описание вакансии

Bloomreach is building the world’s premier agentic platform for personalization.We’re revolutionizing how businesses connect with their customers, building and deploying AI agents to personalize the *entire* customer journey.

  • We're taking autonomous search mainstream, making product discovery more intuitive and conversational for customers, and more profitable for businesses.
  • We’re making conversational shopping a reality, connecting every shopper with tailored guidance and product expertise — available on demand, at every touchpoint in their journey.
  • We're designing the future of autonomous marketing, taking the work out of workflows, and reclaiming the creative, strategic, and customer-first work marketers were always meant to do.

And we're building all of that on the intelligence of a single AI engine — Loomi AI — so that personalization isn't only autonomous…it's also consistent.From retail to financial services, hospitality to gaming, businesses use Bloomreach to drive higher growth and lasting loyalty. We power personalization for more than 1,400 global brands, including American Eagle, Sonepar, and Pandora.

Join our Artificial Intelligence team as a Senior Software Engineer (with an overlap into ML Engineer) and help us revolutionize marketing with ML-powered solutions! You'll work on cutting-edge technologies, impacting millions of users, and contributing to a product that truly makes a difference. Starting monthly compensation begins at 4000 EUR gross, with the final offer tailored for each candidate based on their skills and experience. Stock options and a comprehensive benefits package are also included. Working in one of our Central European offices (Bratislava, Brno, Prague) or from home on a full-time basis, you´ll become a core part of the Engineering Team.

What challenge awaits you?

You'll face the exciting challenge of building and maintaining ML-powered features in a production environment, ensuring they are reliable, scalable, and deliver real value to our users. You'll work alongside a team to overcome the unique challenges of building and running ML models in a SaaS environment, including managing data complexity, optimizing for performance, and ensuring model robustness.

You will cooperate with your teammates, Data Science engineers, and Engineering and Product leaders to speed up ML-powered features' delivery (from ideation to production) by applying principles of continuous discovery, integration, testing, and other techniques from Agile, DevOps, and MLOps mindsets. This will involve building efficient workflows, automating processes, and fostering a culture of collaboration and innovation.

Your job will be to:

a. Design & Deliver new features

  • Translate business requirements for ML-powered features into technical specifications and design documents.
  • Collaborate with data scientists to ensure new ML features' technical feasibility and scalability.
  • Define and develop back-office API endpoints (to configure the features) as well as the high-performance serving endpoints.
  • Develop and implement ML models, algorithms, and data pipelines to support new features.
  • Deploy and monitor new features in production, ensuring seamless integration with existing systems.

b. Ensure quality and performance of developed solution

  • Perform rigorous testing and quality assurance of ML models and code, including unit tests, integration tests, and A/B testing.
  • Implement monitoring systems and dashboards to track the performance of ML models in production, identify potential issues, and optimize for accuracy and efficiency.
  • Contribute to developing and implementing DevOps and MLOps best practices within the team.

c. Support and Maintain owned components

  • Maintain end-to-end features, encompassing back-office APIs, models, definitions, and high-performance serving APIs.
  • Provide ongoing support and maintenance for existing ML-powered features, including troubleshooting issues, fixing bugs, and implementing enhancements.
  • Support our client-facing colleagues in the investigation of possible issues (L3 support).
  • Document code, design decisions, and operational procedures to facilitate ongoing maintenance and knowledge sharing.

What technologies and tools does the AI team work with?

  • Programming languages - Python
  • Google Cloud Platform services - GKE, BigQuery, BigTable, GCS, Dataproc, VertexAI
  • Data Storage and Processing - MongoDB, Redis, Spark, TensorFlow
  • Software and Tools - Grafana, Sentry, Gitlab, Jira, Productboard, PagerDuty

The owned area encompasses various domains such as Predictions, Contextual bandits, Autosegmentation, MLOps. Therefore, having experience in these areas would be beneficial. The team also works with large amounts of data and utilizes platforms and algorithms for model training and data processing & ML pipelines. Experience in these areas is highly valued.

You have the following experience and qualities:

Professional experience

  • Proven experience in Python engineering, with a strong focus on designing and maintaining AI/ML-powered features in production environments.
  • Experience with cloud platforms (e.g., GCP, AWS) and relevant services for ML development and deployment.
  • Solid understanding of software architecture principles, particularly in the context of building and maintaining scalable and reliable APIs and microservices.
  • Experience with version control systems (e.g., Git) and CI/CD pipelines for efficient development and deployment.
  • Familiarity with common ML frameworks, libraries, and tools (e.g., TensorFlow, PyTorch, Scikit-learn, etc.)

Personal qualities

  • A genuine passion for learning new technologies and keeping up-to-date with the latest advancements in AI/ML.
  • Demonstrates strong initiative, ability to work within a team and communication skills
  • A commitment to delivering high-quality work and a dedication to continuous improvement.

Excited? Join us and transform the future of commerce experiences.

#LI-KP1

More things you'll like about Bloomreach:

Culture:

  • A great deal of freedom and trust. At Bloomreach we don’t clock in and out, and we have neither corporate rules nor long approval processes. This freedom goes hand in hand with responsibility. We are interested in results from day one.
  • We have defined our 5 values and the 10 underlying key behaviors that we strongly believe in. We can only succeed if everyone lives these behaviors day to day. We've embedded them in our processes like recruitment, onboarding, feedback, personal development, performance review and internal communication.
  • We believe in flexible working hours to accommodate your working style.
  • We work virtual-first with several Bloomreach Hubs available across three continents.
  • We organize company events to experience the global spirit of the company and get excited about what's ahead.
  • We encourage and support our employees to engage in volunteering activities - every Bloomreacher can take 5 paid days off to volunteer\*.
  • The Bloomreach Glassdoor page elaborates on our stellar 4.4/5 rating. The Bloomreach Comparably page Culture score is even higher at 4.9/5

Personal Development:

  • We have a People Development Program -- participating in personal development workshops on various topics run by experts from inside the company. We are continuously developing & updating competency maps for select functions.
  • Our resident communication coach Ivo Večeřa is available to help navigate work-related communications & decision-making challenges.\*
  • Our managers are strongly encouraged to participate in the Leader Development Program to develop in the areas we consider essential for any leader. The program includes regular comprehensive feedback, consultations with a coach and follow-up check-ins.
  • Bloomreachers utilize the $1,500 professional education budget on an annual basis to purchase education products (books, courses, certifications, etc.)\*

Well-being:

  • The Employee Assistance Program -- with counselors -- is available for non-work-related challenges.\*
  • Subscription to Calm - sleep and meditation app.\*
  • We organize ‘DisConnect’ days where Bloomreachers globally enjoy one additional day off each quarter, allowing us to unwind together and focus on activities away from the screen with our loved ones.
  • We facilitate sports, yoga, and meditation opportunities for each other.
  • Extended parental leave up to 26 calendar weeks for Primary Caregivers.\*

Compensation:

  • Restricted Stock Units or Stock Options are granted depending on a team member’s role, seniority, and location.\*
  • Everyone gets to participate in the company's success through the company performance bonus.\*
  • We offer an employee referral bonus of up to $3,000 paid out immediately after the new hire starts.
  • We reward & celebrate work anniversaries -- Bloomversaries!\*

(\Subject to employment type. Interns are exempt from marked benefits, usually for the first 6 months.)*

Excited? Join us and transform the future of commerce experiences!

If this position doesn't suit you, but you know someone who might be a great fit, share it - we will be very grateful!


Any unsolicited resumes/candidate profiles submitted through our website or to personal email accounts of employees of Bloomreach are considered property of Bloomreach and are not subject to payment of agency fees.

#LI-Remote

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Создайте идеальное резюме с помощью ИИ-агента

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Навыки

  • Git
  • Python
  • PyTorch
  • CI/CD
  • Microservices
  • MLOps
  • DevOps
  • API
  • Redis
  • Scikit-learn
  • Google Cloud Platform
  • Google Kubernetes Engine
  • BigQuery
  • Spark
  • TensorFlow
  • MongoDB
  • BigTable

Возможные вопросы на собеседовании

Проверка опыта интеграции ML-моделей в реальные продукты.

Расскажите о самом сложном случае вывода ML-модели в продакшн: с какими техническими препятствиями вы столкнулись и как их решили?

Оценка навыков оптимизации производительности.

Как бы вы спроектировали высокопроизводительный API для обслуживания ML-моделей, чтобы минимизировать задержку (latency) при миллионах запросов?

Проверка понимания MLOps.

Какие инструменты и подходы вы используете для мониторинга качества моделей в реальном времени и предотвращения деградации данных (data drift)?

Оценка опыта работы с большими данными.

Опишите ваш опыт работы с Google Cloud Platform и Spark для обработки больших объемов данных перед обучением моделей.

Проверка навыков командного взаимодействия.

Как вы обычно организуете процесс передачи модели от Data Science команды в Engineering для обеспечения масштабируемости?

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bloomreach
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