AI Engineer

As 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. • Design, build and deploy LLM-powered agents that improve recommendation and information-retrieval experiences. • Prototype and train ranking/recommendation models from large-scale interaction logs. • Design offline metrics and analyze results. Help set up or monitor online A/B tests; turn findings into iteration plans. • Expose recommendation APIs and integrate them with our existing Go / Ruby services. • Contribute to CI/CD pipelines for data & model versioning (GitHub Actions, Docker). • Code Reviews & Collaboration: Participate in peer reviews; give and receive constructive feedback. Work closely with product owners and teammates to prioritize and scope tasks. • Follow Agile Processes: Adhere to sprint ceremonies, ticketing workflows, and documentation practices. • Monitor & Measure: Assist in establishing basic SLAs and KPIs for service performance; learn to track and report on these metrics.

What makes you a great fit: • 2-3 years of experience in AI Engineering, with significant recent experience designing and deploying Gen AI and LLM-based solutions. • Proven hands-on experience building end-to-end ML/DL pipelines • Bachelor’s or Master’s program in Computer Science, Data Science, Machine Learning, or a related field. • Solid grasp of probability, statistics, linear algebra, and algorithms. • Exposure to LLM-powered agents, familiarity with RAG pipelines, as well as with tool/function calling, multi-step planning and orchestration. • Proficiency in Python; familiarity with at least one ML/RL or deep-learning framework (PyTorch, TensorFlow, JAX). • Experience with SQL (BigQuery, PostgreSQL) and pandas / Spark. • Recommender Systems Exposure • API Know-How: Understanding of REST services and how models are surfaced as endpoints. • Testing & Documentation: Awareness of unit/integration testing for data pipelines and eagerness to learn experiment-driven development. • Soft Skills: Clear communicator who thrives in a fast-paced, collaborative environment. Desirable skills: • Familiarity with real-time stream processing (Kafka, Flink) • Exposure to AWS/GCP AI services • Interest in LLM-based recommendation, embeddings, or content understanding. • Basic knowledge of observability stacks (Prometheus, Grafana) • Comfort with an additional backend language (Go, Node.js, or Ruby) for service integration.

Reasons to apply: • Competitive compensation • Private health insurance • Friendly, diverse, and international work environment • Opportunity to work outside of your comfort zone and develop professionally in an exciting and fast-growing CTV industry. • Change 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. If 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!

Is this you? Titan Operating System S.L. (Titan OS), the Barcelona-based technology, entertainment, and advertising company, is looking for you!  At TitanOS, we live by three core values: • Make things happen – We take ownership, move fast, and deliver impact. • No ego – We collaborate with respect and humility to reach shared goals. • Show genuine passion – We love what we do and never stop learning. Culture 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! Role overview: As 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. Key responsibilities • Design, build and deploy LLM-powered agents that improve recommendation and information-retrieval experiences. • Prototype and train ranking/recommendation models from large-scale interaction logs. • Design offline metrics and analyze results. Help set up or monitor online A/B tests; turn findings into iteration plans. • Expose recommendation APIs and integrate them with our existing Go / Ruby services. • Contribute to CI/CD pipelines for data & model versioning (GitHub Actions, Docker). • Code Reviews & Collaboration: Participate in peer reviews; give and receive constructive feedback. Work closely with product owners and teammates to prioritize and scope tasks. • Follow Agile Processes: Adhere to sprint ceremonies, ticketing workflows, and documentation practices. • Monitor & Measure: Assist in establishing basic SLAs and KPIs for service performance; learn to track and report on these metrics. What makes you a great fit: • 2-3 years of experience in AI Engineering, with significant recent experience designing and deploying Gen AI and LLM-based solutions. • Proven hands-on experience building end-to-end ML/DL pipelines • Bachelor’s or Master’s program in Computer Science, Data Science, Machine Learning, or a related field. • Solid grasp of probability, statistics, linear algebra, and algorithms. • Exposure to LLM-powered agents, familiarity with RAG pipelines, as well as with tool/function calling, multi-step planning and orchestration. • Proficiency in Python; familiarity with at least one ML/RL or deep-learning framework (PyTorch, TensorFlow, JAX). • Experience with SQL (BigQuery, PostgreSQL) and pandas / Spark. • Recommender Systems Exposure • API Know-How: Understanding of REST services and how models are surfaced as endpoints. • Testing & Documentation: Awareness of unit/integration testing for data pipelines and eagerness to learn experiment-driven development. • Soft Skills: Clear communicator who thrives in a fast-paced, collaborative environment. Desirable skills: • Familiarity with real-time stream processing (Kafka, Flink) • Exposure to AWS/GCP AI services • Interest in LLM-based recommendation, embeddings, or content understanding. • Basic knowledge of observability stacks (Prometheus, Grafana) • Comfort with an additional backend language (Go, Node.js, or Ruby) for service integration. Reasons to apply: • Competitive compensation • Private health insurance • Friendly, diverse, and international work environment • Opportunity to work outside of your comfort zone and develop professionally in an exciting and fast-growing CTV industry. • Change 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. If 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!