{"id":838562,"url":"https://alion.io/job/titanos-ai-engineer","title":"AI Engineer","company":{"id":689008,"name":"Titan OS","domain":"titanos.tv","url":"https://alion.io/company/titanos","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"A","score":100,"open_postings":3,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":15,"computed_at":"2026-10-01T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","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":53000,"max_usd":127000,"period":"year","method":"role_country_seniority_unknown","sample_n":21},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Agile","optional":false},{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Function Calling","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Go","optional":false},{"name":"Google BigQuery","optional":false},{"name":"JAX","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Rest API","optional":false},{"name":"Ruby","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Apache Kafka","optional":true},{"name":"AWS","optional":true},{"name":"Embeddings","optional":true},{"name":"Flink","optional":true},{"name":"GCP","optional":true},{"name":"Grafana","optional":true},{"name":"JavaScript","optional":true},{"name":"Node JS","optional":true},{"name":"Prometheus","optional":true}],"status":"live","first_seen_at":"2026-09-30T10:05:56Z","employer_posted_date":"2026-09-30","last_verified_at":"2026-09-30T23:16:38Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Is this you?\nTitan Operating System S.L. (Titan OS), the Barcelona-based technology, entertainment, and advertising company, is looking for you!\nAt TitanOS, we live by three core values:\nMake things happen - We take ownership, move fast, and deliver impact.\nNo ego - We collaborate with respect and humility to reach shared goals.\nShow genuine passion - We love what we do and never stop learning.\nCulture and environment are at the heart of our ethos. If the above resonates with you, keep reading because we believe you could be a perfect addition to our incredible team!\nRole overview:\nAs an AI & Content-Recommendation Engineer, you’ll work with our Machine-Learning and Backend teams to design, train, and deploy the models and data pipelines that decide “what to watch next” on our Smart TV platform. You’ll gain hands-on experience across the full ML lifecycle - from exploratory data analysis through online A/B testing - while shipping features used by millions of viewers worldwide.\nKey responsibilities\nDesign, build and deploy LLM-powered agents that improve recommendation and information-retrieval experiences.\nPrototype and train ranking/recommendation models from large-scale interaction logs.\nDesign offline metrics and analyze results. Help set up or monitor online A/B tests; turn findings into iteration plans.\nExpose recommendation APIs and integrate them with our existing Go / Ruby services.\nContribute to CI/CD pipelines for data & model versioning (GitHub Actions, Docker).\nCode Reviews & Collaboration: Participate in peer reviews; give and receive constructive feedback. Work closely with product owners and teammates to prioritize and scope tasks.\nFollow Agile Processes: Adhere to sprint ceremonies, ticketing workflows, and documentation practices.\nMonitor & Measure: Assist in establishing basic SLAs and KPIs for service performance; learn to track and report on these metrics.\nRequirements\nWhat makes you a great fit:\n2-3 years of experience in AI Engineering, with significant recent experience designing and deploying Gen AI and LLM-based solutions. \nProven hands-on experience building end-to-end ML/DL pipelines\nBachelor’s or Master’s program in Computer Science, Data Science, Machine Learning, or a related field.\nSolid grasp of probability, statistics, linear algebra, and algorithms.\nExposure to LLM-powered agents, familiarity with RAG pipelines, as well as with tool/function calling, multi-step planning and orchestration.\nProficiency in Python; familiarity with at least one ML/RL or deep-learning framework (PyTorch, TensorFlow, JAX).\nExperience with SQL (BigQuery, PostgreSQL) and pandas / Spark.\nRecommender Systems Exposure\nAPI Know-How: Understanding of REST services and how models are surfaced as endpoints.\nTesting & Documentation: Awareness of unit/integration testing for data pipelines and eagerness to learn experiment-driven development.\nSoft Skills: Clear communicator who thrives in a fast-paced, collaborative environment.\nDesirable skills:\nFamiliarity with real-time stream processing (Kafka, Flink)\nExposure to AWS/GCP AI services\nInterest in LLM-based recommendation, embeddings, or content understanding.\nBasic knowledge of observability stacks (Prometheus, Grafana)\nComfort with an additional backend language (Go, Node.js, or Ruby) for service integration.\nBenefits\nReasons to apply:\nCompetitive compensation\nPrivate health insurance\nFriendly, diverse, and international work environment\nOpportunity to work outside of your comfort zone and develop professionally in an exciting and fast-growing CTV industry.\nChange the future of TV! A unique opportunity to join a well-funded, high-growth company in the early stages to help shape a product/business that will impact millions.\nIf you're excited about this position, don’t hesitate to apply. We’re waiting for you to join us! And if you want to know more about us, follow us on LinkedIn!","description_format":"text","description_chars":3905,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Health insurance"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Operating Systems","Streaming & OTT Platforms"],"lifecycle":[{"event":"open","at":"2026-09-12T20:26:26Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":0,"expected_fill_days":15,"reasons":["conf:6","velocity","win:early"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/titanos-ai-engineer","json_url":"https://alion.io/job/titanos-ai-engineer.json","meta":{"generated_at":"2026-10-01T09:38:07Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":333,"day_limit":5000,"remaining_today":4667,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}