AI Engineer
Indexed description
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
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
- 2-3 years of experience in AI Engineering, with significant recent experience designing and deploying Gen AI and LLM-based solutions.
- 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
- 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
- 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
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