Must have 5+ years of hands-on experience in Machine Learning systems, Search, Information Retrieval (IR), NLP
Mandatory (Experience 2)
Experience building and deploying scalable ML/AI systems for ranking, personalization, recommendation, or enterprise search use cases.
Mandatory (Experience 3)
Hands-on experience in NLP-based search applications, embeddings, semantic search, taxonomy/ontology models, metadata-driven retrieval, or recommendation systems.
Mandatory (Experience 4)
Strong experience in designing and optimizing search systems including indexing, query relevance, semantic retrieval, faceted search, ranking, and search accuracy improvements.environments.
Mandatory (Experience 5)
Strong programming expertise in Python, Java, or Scala with good understanding of data structures, algorithms, OOP concepts, and Linux
Mandatory (Core Skills) Expertise in Information Retrieval, Search Technologies, NLP, Machine Learning, TensorFlow/PyTorch/scikit-learn/Keras, indexing, query optimization, semantic search, ranking systems, and search relevance tuning.
Mandatory (Database & Infrastructure)
Experience working with SQL/NoSQL databases such as MongoDB, Cosmos DB, Cassandra, or similar distributed data systems.
Mandatory (CI/CD & Engineering Practices)
Hands-on experience with CI/CD pipelines, Git, Jenkins, testing frameworks, monitoring, and production-grade software engineering practices.
Mandatory (Problem Solving)
Strong analytical thinking, debugging capabilities, performance optimization skills, and ability to independently resolve complex technical issues related to search quality, scalability, and latency.
Mandatory (Production Deployment)
Experience deploying scalable AI/ML or search systems in production environments with high availability and performance
requirements
. • Mandatory (Company) - Preferred candidates from AI-first startups, search/recommendation platforms, SaaS organizations, fintech, e-commerce, product-based companies, or large-scale data-driven enterprises. • Mandatory (Age Criteria) Preferred age bracket: Up to 30 years. • Preferred (Experience 1) Experience with Elasticsearch, Solr, Lucene, vector databases, semantic retrieval systems, or enterprise search platforms. • Preferred (Experience 2)Exposure to personalization/recommendation systems • Preferred (Experience 3) Experience with Docker, Kubernetes, AWS/Azure/GCP. • Preferred (Experience 4) Mentoring or technical leadership exposure is a plus Skills: optimization,ai,ci,cd,ml,data,nlp,data scientist