{"id":2176502,"url":"https://alion.io/job/elsevier-senior-mlops-engineer","title":"Senior MLOps Engineer","company":{"id":3090,"name":"Elsevier","domain":"elsevier.com","url":"https://alion.io/company/elsevier","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mexico City, Mexico"],"countries":["MX"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":115400,"max":192300,"currency":"USD","period":"year","gross":null,"usd_annual":192300},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"AI Agents","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"ElasticSearch","optional":false},{"name":"Embeddings","optional":false},{"name":"Java","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Neo4j","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenSearch","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Scala","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Spark","optional":false},{"name":"Structured Outputs","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-09-14T00:00:00Z","employer_posted_date":"2026-09-14","last_verified_at":"2026-10-12T02:26:16Z","board_verified":true,"closed_at":null,"days_open":28,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":28},"description":"Are you passionate about building scalable AI and machine learning systems that power world-leading research and healthcare platforms?\nDo you enjoy turning cutting-edge NLP, search, recommendation, and Generative AI innovations into reliable, secure, and production-ready solutions that create real-world impact?\nAbout our Team\nOur global team support products education electronic health records that introduce students to digital charting and prepare them to document care in today’s modern clinical environment. We have a very stable product that we’ve worked to get to and strive to maintain. Our team values trust, respect, collaboration, agility, and quality.\nAbout the Role\nJoin the team that powers Elsevier’s research platforms-Scopus/Scopus AI, ScienceDirect/ScienceDirect AI, and journal submission & peer review workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world’s largest scholarly corpora, so you’ll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality.\nKey Responsibilities\nML & LLM Engineering, Search and Recommendation Engines\nAutomate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI)\nMaintain and version model registries and artifact stores to ensure reproducibility and governance\nDevelop and manage CI/CD for ML, including automated data validation, model testing, and deployment.\nImplement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML.\nEnd-to-end custom SageMaker pipelines for recommendation systems.\nDesign and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted\nDesign and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs \nBuild evaluation pipelines: offline IR metrics (e.g., NDCG, MAP, MRR), LLM quality metrics (e.g., faithfulness, grounding), and A/B testing.\nOptimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization\nStay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems\nCollaboration\nPartner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions\nCollaborate and interface with Operations Engineers who deploy and run production infrastructure.\nRequired Qualifications\n3-5+ years in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production.\nStrong Python, Java, and/or Scala engineering\nExperience with statistical analysis, machine learning theory and natural language processing\nHands-on- experience with major cloud vendor solutions (AWS,Azureand/or Google)\nSearch/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr/ Neo4j).\nExperience in evaluating LLM models\nBackground with scholarly publishing workflows, bibliometrics, or citation graphs\nA strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics\nFamiliarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark\nExperience with large scale data processing systems, e.g., Spark\nWork in a Way That Works for You\nWe promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance, and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.\nThis is a hybrid role in Mexico City (Reforma) Our teams operate in a flexible hybrid work model, combining in-person collaboration with remote flexibility. You’ll be expected to participate in regular team meetings and engineering rituals in line with your team’s cadence.\nWorking Pattern\nWorking flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.\nWe know that your well-being and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:\nPrivate Medical, Dental and Vision Plan, coverage for employee and eligible dependents\n\nSavings Fund with company matching contributions\n\nComprehensive life insurance policy\n\nGrocery voucher\n\nVacation Bonus, salary supplement based on vacation days taken\n\nMinor medical expenses discount card for minor medical expenses and outpatient services\n\nAccess to learning and development resources\n\nSupport for personal and work-related challenges through an Employee Assistance Programme\n\nAwards to recognise key service milestones\n\nTime off to support the charities and causes that matter to you\n\nAbout the Business\nA global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world's grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.\n\nU.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates.\n\nWe know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Clickhereto access benefits specific to your location.\nWe are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.\nCriminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scamshere.\nPlease read our Candidate Privacy Policy.\nWe are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.\nUSA Job Seekers:\nEEO Know Your Rights.","description_format":"text","description_chars":6998,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Hybrid work","Life insurance","Parental leave"],"hiring_locations":[{"name":"Mexico","iso":"MX","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Publishing","Financial Data & Market Intelligence"],"lifecycle":[{"event":"open","at":"2026-10-09T14:09:40Z"}],"visa":[],"liveness":{"score":54,"band":"ok","label":"Likely open","p_open":1,"p_active":0.721,"p_room":0.75,"age_days":26,"expected_fill_days":29,"reasons":["conf:6","win:late","comp:brand"],"computed_at":"2026-10-10T05:45:15Z"},"pay":{"stated_usd_annual":192300,"is_top_pay":false},"html_url":"https://alion.io/job/elsevier-senior-mlops-engineer","json_url":"https://alion.io/job/elsevier-senior-mlops-engineer.json","meta":{"generated_at":"2026-10-12T03:41:19Z","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":5703,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-13T00:00:00Z"}},"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":3090},"rest":"https://alion.io/mcp/rest/get_company?id=3090"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Felsevier-senior-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%2Felsevier-senior-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%2Felsevier-senior-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/elsevier-senior-mlops-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Felsevier-senior-mlops-engineer"}]}