{"id":711463,"url":"https://alion.io/job/wallapop-mlops-engineer","title":"MLOps Engineer","company":{"id":53727,"name":"Wallapop","domain":"wallapop.com","url":"https://alion.io/company/wallapop","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":75,"open_postings":4,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Barcelona, Spain"],"countries":["ES"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":46000,"max_usd":105000,"period":"year","method":"role_country_seniority_unknown","sample_n":30},"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Feast","optional":false},{"name":"Flyte","optional":false},{"name":"Git","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"OpenSearch","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"TensorFlow","optional":false},{"name":"Vertex AI","optional":false},{"name":"Agile","optional":true},{"name":"Amazon S3","optional":true},{"name":"Amazon SageMaker","optional":true},{"name":"AWS Lambda","optional":true},{"name":"Azure","optional":true},{"name":"dbt","optional":true},{"name":"GCP","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"LlamaIndex","optional":true},{"name":"RAG","optional":true},{"name":"Spark","optional":true},{"name":"Wi-Fi","optional":true},{"name":"Windows","optional":true}],"status":"live","first_seen_at":"2025-12-19T12:16:56Z","employer_posted_date":"2026-07-16","last_verified_at":"2026-10-17T16:07:56Z","board_verified":true,"closed_at":null,"days_open":302,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":301},"description":"Wallapop is a Barcelona based scale-up driven by the purpose to empower people to embrace a more conscious and human way of consumption. We believe in a world where collaborative economy is mainstream. This is what drives us. \nWallapop operates in Spain, Italy and Portugal, offering a catalogue of several hundreds of millions of products and services. Powered by technical innovation and continuous improvement, we bring together the scale & trust of classifieds with the marketplace’s convenience & reach. Our mission is to enable a connected trade ecosystem, making 2nd-hand the norm through smart use of technology.\nThe Challenge\nWallapop generates billions of data points daily. With a mature data infrastructure already in place, our Data Science and Machine Learning area is gaining significant momentum. As we scale, we face the exciting challenge of taking our ML Platform to the next level to support complex solutions in Personalization, Search, Trust & Safety, and Logistics. As an ML Engineer (MLOps), you will contribute to the evolution of our ML Platform and MLOps practice. You will partner with Data Scientists, Data Engineers, and DevOps to collaborate on a vision that balances innovation with reliability, ensuring our models scale efficiently to serve millions of users.\nWhat You Will Do\nIterate and maintain Wallapop’s ML Platform, identifying opportunities to improve speed, reliability, and maintainability. You will help execute the long-term vision and roadmap for MLOps.\n\nWork hand-in-hand with Data Scientists to support their efforts, ensuring they have the tooling to develop, deploy, and monitor scalable models efficiently.\n\nAdopt and promote engineering best practices (coding standards, testing, CI/CD) within the ML domain.\n\nPartner with Data Engineering and DevOps to align ML development with company-wide infrastructure and data governance standards.\n\nInvestigate and integrate new frameworks and tools (e.g., for LLMs or real-time inference) to keep our stack modern and effective.\n\nWhat We’re Looking For\nSolid experience contributing to and maintaining production-ready ML platforms and pipelines. You understand the lifecycle from experimentation to monitoring.\n\nSolid understanding of AWS components (SageMaker, Lambda, S3) and container orchestration with Kubernetes.\n\nStrong software engineering background with proficiency in Python, Git, and CI/CD workflows. You write robust, testable code.\n\nExperience with real-time ML architectures, leveraging tools like Kafka for low-latency ingestion and inference.\n\nHands-on experience with vector databases or semantic search infrastructure (e.g., OpenSearch, Vertex AI), including indexing and retrieval tuning.\n\nFamiliarity with the broader ML toolkit, such as orchestration/tracking tools (Flyte, MLFlow, Feast) and standard libraries (Pandas, Scikit-learn, TensorFlow/PyTorch).\n\nProfessional proficiency in English, with the ability to communicate technical concepts clearly to diverse stakeholders.\n\nWhat Would Be A Plus\nHands-on experience working with LLMs, RAG architectures, and libraries like LangChain or LlamaIndex.\n\nFamiliarity with Big Data technologies like Spark or Beam.\n\nExperience with Data Engineering tools such as Airflow, dbt, or Datahub.\n\nExperience with other cloud platforms like GCP or Azure in addition to AWS.\n\nDo note that all our jobs are Barcelona based. We follow a hybrid model where flexibility rules. We commit to a minimum of 6 days per month in the office. Each team self-organizes to decide on cadence and in-person/remote rituals.\nWallapop is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees as we want Wallapop to be a place for everyone.\nAdditionally to the opportunity to contribute to an agile product set up and work together towards achieving our meaningful mission, we offer the following Perks & Benefits:\nGenerous individual learning budget of 2k per year\nFree office meals, lunch selection from different providers\nGroup and individual English, Catalan & Spanish lessons as part of our working day\nPrivate Health Insurance with Alan\nFlexible working hours + intensive Fridays\nFlexible remuneration to deduct from gross salary (kindergarten/food/transport check)\nGym & Wellness plan, including physiotherapist in the office\nGenerous referral Program & Charity Donation\nBonus for weddings & newborns\nWallapop Renta (Tax income support)\nMonthly plan for free shipping, bumps & home-pick-up on our services\nWork anniversary Gifts and Birthday Surprises\nContribution towards your WIFI in your monthly payroll\nOne-off payment based on compensation package to go towards setting up your home office\nRelocation package (monetary support and legal advice) and visa sponsorship, if applicable\n26 holidays per year\nTOP hardware of your choice (latest Apple or Windows)\nWhat does the hiring process for this position look like? **Please, note that all interviews take place remotely over hangouts.**\nIntro Call - run by Talent Acquisition, focus on providing more information about the role and the company as well as going over your experience, motivation, and expectations. This usually takes 45-60 minutes.\nCase Study - you will be working in a case study to assess the technical skills required for the role. \nExpertise Interview - run by the core team, focusing on the hard skills and the ability to deliver in a given context. This usually takes 60-90 minutes.\nStakeholder Interview - run by the hiring team and relevant stakeholders, focus on the ability to collaborate & deliver in a cross-functional set-up. This usually takes 60 minutes.\nCulture-Add Interview - run by culture interviewers, focus on adherence to Wallapop's purpose and business proposition. This usually takes 60 minutes.\n Offer - should you be the right candidate, your offer will be discussed over a call with talent acquisition and will then be confirmed in writing.","description_format":"text","description_chars":5953,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"Advanced (C1)","optional":false}]},"benefits":["Flexible schedule","Health insurance","Home office","Office meals"],"hiring_locations":[{"name":"Spain","iso":"ES","kind":"country"}],"hiring_excludes":[],"relocation_offered":true,"industries":["Marketplaces","Secondhand"],"lifecycle":[{"event":"open","at":"2026-09-11T04:56:33Z"}],"visa":[],"liveness":{"score":4,"band":"cold","label":"Long shot","p_open":1,"p_active":0.133,"p_room":0.28,"age_days":301,"expected_fill_days":27,"reasons":["conf:2","win:tail","crowd:"],"computed_at":"2026-10-17T05:46:00Z"},"pay":null,"html_url":"https://alion.io/job/wallapop-mlops-engineer","json_url":"https://alion.io/job/wallapop-mlops-engineer.json","meta":{"generated_at":"2026-10-17T17:00:04Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":23377,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":53727},"rest":"https://alion.io/mcp/rest/get_company?id=53727"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fwallapop-mlops-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fwallapop-mlops-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fwallapop-mlops-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/wallapop-mlops-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fwallapop-mlops-engineer"}]}