{"id":1021410,"url":"https://alion.io/job/opentable-senior-data-engineer-aiml","title":"Senior Data Engineer (AI/ML)","company":{"id":450225,"name":"OpenTable","domain":"opentable.com","url":"https://alion.io/company/opentable-5","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":90,"open_postings":13,"ghost_share":0,"stale_share":0.385,"repost_share":0,"time_to_fill_p50_days":43,"computed_at":"2026-11-03T05:54:40Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Delhi, India","India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":43000,"period":"year","method":"role_seniority_country_cell","sample_n":81},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Airflow","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Embeddings","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Function Calling","optional":false},{"name":"Java","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Scala","optional":false},{"name":"Semantic Search","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Apache Kafka","optional":true},{"name":"CI/CD","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"LlamaIndex","optional":true},{"name":"MLFlow","optional":true},{"name":"Pinecone","optional":true},{"name":"Qdrant","optional":true},{"name":"Slack","optional":true},{"name":"Weaviate","optional":true}],"status":"live","first_seen_at":"2026-09-18T06:05:25Z","employer_posted_date":"2026-09-18","last_verified_at":"2026-11-03T12:55:46Z","board_verified":true,"closed_at":null,"days_open":46,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":46},"description":"This role is 100% remote across India location\n About OpenTable\nWith millions of diners, 70,000+ restaurant partners and 25+ years of experience, OpenTable, part of Booking Holdings, Inc. (NASDAQ: BKNG), is an industry leader with a passion for helping restaurants thrive. Our world-class technology empowers restaurants to focus on what matters most - their team, their guests, and their bottom line - while enabling diners to discover and book the perfect restaurant for every occasion. \nEvery employee at OpenTable has a tangible impact on what we do and how we do it. You’ll also be part of a global team and its portfolio of metasearch brands. Hospitality is all about taking care of others, and it defines our culture.\nAbout Role\nWe are looking for a Senior Data Engineer - AI/ML to help build the data and AI infrastructure powering our next generation of intelligent products and experiences.\nThis role combines modern data engineering with Generative AI. You will design scalable data platforms and pipelines while building production-grade solutions using LLMs, RAG, embeddings, vector search, and AI agents. You will work closely with data scientists, ML engineers, software engineers, and product teams to turn AI capabilities into reliable, scalable production systems.\nWhat You'll Do\nDesign and build AI/LLM data pipelines supporting training, inference, evaluation, embeddings, and retrieval workloads.\n\nBuild production-grade RAG systems, including ingestion, chunking, embedding generation, indexing, retrieval, reranking, and context construction.\n\nDevelop AI applications using LLMs, structured outputs, function/tool calling, and agentic workflows.\n\nBuild and optimize semantic search and vector retrieval systems.\n\nDevelop frameworks for LLM evaluation, monitoring, tracing, quality measurement, latency, and cost optimization.\n\nDesign scalable batch and streaming pipelines using Databricks, Apache Spark, Delta Lake, Snowflake, and Airflow.\n\nBuild data products and platforms that make structured and unstructured enterprise data accessible to AI applications.\n\nDevelop reliable ETL/ELT pipelines and optimize large-scale distributed workloads for performance and cost.\n\nEstablish data quality, governance, lineage, security, and observability practices.\n\nPartner with ML and application engineering teams to move AI prototypes into production-ready systems.\n\nRequired Qualifications\n5+ years of experience in data engineering, software engineering, distributed systems, or a related field.\n\nStrong programming skills in Python and/or Scala/Java and advanced SQL.\n\nHands-on experience with Databricks, Snowflake, Apache Spark, Delta Lake, and Airflow.\n\nStrong experience with cloud data platforms such as Snowflake and/or Databricks.\n\nPractical experience building applications using LLMs or Generative AI.\n\nStrong understanding of RAG architectures, embeddings, vector databases, semantic search, and retrieval systems.\n\nFamiliarity with LLM concepts including prompting, structured outputs, tool calling, and model evaluation.\n\nExperience designing scalable, reliable, and observable production data systems.\n\nPreferred Qualifications\nDeep experience designing large-scale data platforms, distributed processing systems, and complex data workflows.\n\nStrong experience with real-time and streaming data architectures, including Kafka, Spark Structured Streaming, or similar technologies.\n\nExperience building low-latency data pipelines and event-driven architectures.\n\nExperience designing complex multi-stage ETL/ELT and data orchestration workflows using Airflow or similar platforms.\n\nExperience optimizing Spark/Databricks workloads, including partitioning, clustering, caching, joins, and compute optimization.\n\nExperience building data platforms supporting both batch and real-time AI/ML workloads.\n\nExperience with LLM and AI evaluation frameworks, including automated evaluations, offline/online evaluation, quality metrics, and experimentation.\n\nExperience building evaluation datasets and pipelines for measuring LLM/RAG/agent quality, accuracy, relevance, latency, and cost.\n\nExperience with AI observability and tracing, including token usage, model performance, latency, failures, and production monitoring.\n\nExperience with LangGraph, LangChain, LlamaIndex, or similar AI orchestration frameworks.\n\nExperience with vector databases such as Qdrant, Pinecone, Weaviate, or Databricks Vector Search.\n\nExperience with Kafka, MLflow, Unity Catalog, Databricks Mosaic AI, or model-serving platforms.\n\nExperience building data quality, lineage, governance, and data/AI observability frameworks.\n\nStrong understanding of distributed systems, cloud architecture, APIs, CI/CD, and production operations.\n\nImpact\nYou will help build the data and AI foundation for intelligent products, combining large-scale data engineering, streaming systems, and modern Generative AI to deliver reliable, scalable, measurable, and production-ready AI systems.\nBenefits\nWork from (almost) anywhere for up to 20 days per year\n\nFocus on mental health and well-being:\n\nCompany-paid therapy sessions through SpringHealth\n\nCompany-paid subscription to Headspace\n\nAnnual company-wide week off a year - the whole team fully recharges (and returns without a pile-up of work!)\n\nPaid parental leave\n\nGenerous paid vacation + time off for your birthday\n\nPaid volunteer time\n\nFocus on your career growth:\n\nDevelopment Dollars\n\nLeadership development\n\nAccess to thousands of on-demand e-learnings\n\nTravel Discounts\n\nEmployee Resource Groups\n\nQuarterly team offsites\n\nTax optimisation options\n\nGenerous health insurance\n\nPension fund\n\nWork Environment & Flexibility\nAt OpenTable, we pride ourselves on fostering a global and dynamic work environment. As a team member with us, you will benefit from a schedule tailored to accommodate a global workforce operating across multiple time zones. While the majority of your responsibilities may align with conventional business hours, there will be instances where you are expected to manage communications - via calls, Slack messages, or emails - outside of regular working hours to effectively collaborate with international colleagues, respond to restaurant partners, and/or address urgent matters. OpenTable will always abide by and consider local laws and regulations.\nInclusion\nWe’re committed to creating a workplace where everyone feels they belong and can thrive. We know the best ideas come when we bring different voices to the table, so we're building a team as dynamic as the diners and restaurants we serve-and fostering a culture where everyone feels welcome to be themselves.\nIf you need accommodations during the application or interview process, or on the job, we’re here to support you. 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