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10 месяцев назад

Machine Learning Engineer (MLOps)

Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Английский
c1
Страна
Spain
Релокация
Spain
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Senior Machine Learning Engineer (MLOps): Building and optimizing Wallapop's ML Platform and MLOps practices with an accent on improving speed, reliability, and maintainability. Focus on defining the long-term vision and roadmap for MLOps and integrating new frameworks for scalable model deployment and monitoring.

Location: Must be based in Barcelona, Spain or be able to relocate to Spain. This is a hybrid role requiring a minimum of 6 days per month in the office.

Company

hirify.global is a Barcelona-based scale-up empowering conscious consumption and operating a marketplace for unique goods and services in Spain, Italy, and Portugal.

What you will do

  • Iterate and maintain hirify.global’s ML Platform, defining its long-term vision and roadmap for MLOps.
  • Partner with Data Scientists to provide tooling for developing, deploying, and monitoring scalable models efficiently.
  • Define and promote engineering best practices, including coding standards, testing, and CI/CD within the ML domain.
  • Align ML development with company-wide infrastructure and data governance standards through collaboration with Data Engineering and DevOps.
  • Investigate and integrate new frameworks and tools, such as for LLMs or real-time inference, to keep the tech stack modern.

Requirements

  • Proven experience building and owning production-ready ML platforms and pipelines, understanding the full lifecycle from experimentation to monitoring.
  • Deep understanding of AWS components (SageMaker, Lambda, S3) and container orchestration with Kubernetes.
  • Strong software engineering background with proficiency in Python, Git, and CI/CD workflows.
  • Experience with real-time ML architectures, leveraging tools like Kafka for low-latency ingestion and inference.
  • Hands-on experience with vector databases or semantic search infrastructure (e.g., OpenSearch, Vertex AI).
  • Familiarity with orchestration/tracking tools (Flyte, MLFlow, Feast) and standard ML libraries (Pandas, Scikit-learn, TensorFlow/PyTorch).
  • Professional proficiency in English and Spanish.

Nice to have

  • Hands-on experience working with LLMs, RAG architectures, and libraries like LangChain or LlamaIndex.
  • Familiarity with Big Data technologies like Spark or Beam.
  • Experience with Data Engineering tools such as Airflow, dbt, or Datahub.
  • Experience with other cloud platforms like GCP or Azure in addition to AWS.

Culture & Benefits

  • Competitive phantom shares package for all employees.
  • Generous individual learning budget of 2k per year.
  • Group and individual English, Catalan & Spanish lessons.
  • Private Health Insurance with Alan.
  • Flexible working hours and intensive Fridays.
  • Flexible remuneration options (kindergarten/food/transport check).
  • Gym & Wellness plan, including physiotherapist in the office.
  • Generous referral Program & Charity Donation.
  • Bonus for weddings & newborns, and hirify.global Renta (Tax income support).
  • Monthly plan for free shipping, bumps & home-pick-up on hirify.global services.
  • Work anniversary Gifts and Birthday Surprises.
  • Contribution towards your WIFI and a one-off payment for home office setup.
  • Relocation package (monetary support and legal advice) and visa sponsorship, if applicable.
  • 26 holidays per year and top hardware of your choice (latest Apple or Windows).

Hiring process

  • Intro Call (45-60 minutes) with Talent Acquisition.
  • Technical Task to assess required technical skills.
  • Expertise Interview (60-90 minutes) with the core team.
  • Stakeholder Interview (60 minutes) with the hiring team and relevant stakeholders.
  • Culture-Add Interview (60 minutes) with culture interviewers.
  • Offer discussion and written confirmation. All interviews take place remotely over hangouts.

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