*location*: remote work (mexico specific)
*work timings: monday-friday*
*hours: 8-5 pm cst*
*responsibilities*:
- design and implement machine learning models for search and ranking (e.g., metadata classifiers, embedding models, and reranking algorithms).
- develop and optimize scalable pipelines for data ingestion, enrichment, and indexing.
- build and deploy embedding-based models for hybrid search systems, ensuring high performance and low latency.
- collaborate with backend teams to integrate redis caching and semantic search solutions.
- work with external ai/ml apis (e.g., openai) to enhance system capabilities.
- monitor and fine-tune search ranking algorithms to improve relevance metrics.
- create semantic caching strategies and ensure seamless integration with the hybrid search db.
*requirements*:
- strong understanding of ml fundamentals, including nlp techniques, embeddings, and ranking models.
- proficiency in python, tensorflow, pytorch, or similar ml frameworks.
- experience with search technologies (e.g., elasticsearch, vector search systems).
- familiarity with aws services (e.g., lambda, s3) and scalable architectures.
- knowledge of data scraping and processing pipelines.
- hands-on experience integrating and optimizing external ai apis (e.g., openai).
- excellent problem-solving skills and ability to work in a microservices-based environment.
pay: from $85,000.00 per year
*experience*:
- python: 4 years (required)
- aws: 4 years (required)
- machine learning: 4 years (required)
- nlp: 4 years (required)