The Role

Reporting to the Founder/CEO, build a next-gen media engagement platform focusing on contextual understanding, personalized experiences and scalable infrastructure. Drive technical architecture while owning key implementations across user profiling, recommendations, and core platform services.

Email resume to [email protected].

Responsibilities

-User Understanding & Engagement

• Design and implement contextual user profiling systems
• Build sports interest and behavior graph models
• Create natural language processing pipelines for sports context
• Develop real-time engagement scoring systems
• Implement multi-modal content understanding
• Set up personalization engines

-Smart Recommendations & Content

• Build learning path recommendation engines
• Develop event and offer matching systems
• Create purchase prediction models
• Implement real-time content enhancement
• Design A/B testing frameworks
• Set up content personalization pipelines

-Platform Infrastructure (Supporting Systems)

• Design and implement FastAPI microservices
• Build secure payment and subscription systems
• Create data pipelines for behavior analysis
• Implement tracking and attribution systems
• Set up multi-tenant architecture
• Manage AWS cloud infrastructure

Technical Stack

User Profiling:

• Graph DB: Neo4j, Neptune

• Analysis: GraphQL, Cypher

• Real-time: Interest scoring, Affinity modeling

Smart Recommendations:

• Engines: Collaborative filtering, Content-based

• Processing: Real-time scoring, Contextual ranking

• Integration: Event APIs, Offer management

Supporting Infrastructure:

Cloud: AWS (primary), GCP/Azure/Supabase experience valuable

AI/ML Services:

• AWS: SageMaker, Bedrock, Comprehend
• General: PyTorch/TensorFlow, Claude API

Vector Databases:

• AWS: OpenSearch, Neptune
• General: Pinecone, Weaviate

Payment Systems:

• Processing: Stripe, Payment intents
• Security: PCI compliance, Tokenization

Technical Requirements

Essential Skills

- Strong graph database and user modeling experience

- Background in recommendation systems

- NLP / Real-time ML inference expertise

- AWS infrastructure experience

- Python backend development

- React/TypeScript frontend development

AI/ML Requirements

- Experience integrating and fine-tuning multiple LLMs (e.g., Claude, GPT)

- Practical knowledge of vector databases and hybrid search architectures

- Track record of deploying real-time ML inference systems at scale

- Experience building and maintaining knowledge graphs

- Understanding of ML model deployment and monitoring in production

- Background in content enhancement and NLP pipelines

- Ability to optimize model performance and costs

- Experience with ML feature engineering and data pipelines

Additional Skills (nice to have)

- Payment system implementation

- Vector database optimization

- Event streaming platforms

- Security best practices

- ML infrastructure optimization

- Performance monitoring

Impact

Join an early-stage startup working with major media partners. Shape core architecture decisions and build systems that make stories more accessible and enjoyable for everyone.