Job
Description
Job Summary: We are looking for a passionate and skilled AI/ML Engineer to join our team, focusing on cutting edge solutions in vector search, embeddings, and semantic similarity. In this role, you will design, develop, and optimize intelligent search systems that leverage state-of-the-art machine learning and deep learning techniques. You will collaborate with cross-functional teams to build scalable and efficient solutions that transform how we retrieve and process information. Key Responsibilities: Develop and Optimize Vector Search Systems: Implement advanced vector-based search algorithms using frameworks like FAISS, Milvus, Weaviate, or Pinecone to enable high-performance retrieval systems. Design Semantic Search Solutions: Apply semantic similarity techniques to enable precise and context-aware search experiences. Research and Experimentation: Stay updated on advancements in NLP, ANN (Approximate Nearest Neighbor) search, and embedding models; experiment with new tools and techniques to improve system performance. Collaboration and Documentation: Collaborate with data scientists, backend engineers, and product teams, and document methodologies and findings effectively. Required Skills Machine Learning Expertise: Hands-on experience with ML frameworks NLP Knowledge: Strong understanding of natural language processing, embeddings, and transformer-based models (e.g., BERT, RoBERTa, GPT). Vector Search Tools: Proficiency in tools like FAISS, Milvus, Pinecone, or other ANN libraries. Search Algorithms: In-depth knowledge of similarity search techniques, including cosine similarity, dot-product scoring, and clustering methods. Programming Skills: Strong coding abilities in Python (experience with libraries like NumPy, Pandas, Scikit-learn, Hugging Face Transformers, etc.). Cloud/DevOps Knowledge: Familiarity with cloud platforms (Azure) and containerization/orchestration tools like Docker and Kubernetes. Preferred Skills Experience with hybrid search techniques combining traditional search (e.g., Elasticsearch, Solr) and vector search. Knowledge of vector quantization techniques for optimized storage and retrieval. Background in information retrieval, knowledge graphs, or recommendation systems. Key Traits: Should have excellent communication skills. Should be self motivated and willing to work as part of a team. Should be able to collaborate and coordinate with offshore and onshore teams. Be a problem solver and be proactive to solve the challenges that come his/her way.
