Job description
OUR CLIENT
Our client provides data-driven, action-oriented solutions to business problems through statistical data mining, cutting-edge analytics techniques, and a consultative approach. Leveraging proprietary methodology and best-of-breed technology, our client's analytics team takes an industry-specific approach to transform decision-making and embed analytics more deeply into their business processes. They have a global footprint of 2,000+ data scientists and analysts who assist client organizations with complex risk minimization methods, advanced marketing, pricing and CRM strategies, internal cost analysis, and cost and resource optimization within the organization. They serve the insurance, healthcare, banking, capital markets, utilities, retail and e-commerce, travel, transportation and logistics industries.
ROLE
We are seeking (2) Vector Database Engineers with experience in designing, implementing, and optimizing vector databases related to Large Language Models (LLMs). The candidate should have strong experience in fundamental data engineering concepts automated pipeline build, CI/ CD using Azure cloud. Candidate should be able to communicate technical concepts effectively to both technical and non-technical stakeholders
RESPONSIBILITIES
4.5+ years of experience in deploying data engineering solutons.
3+ years of Data Engineering experience comprising of - database solutions, CI/CD pipelines, automated deployment/ testing in Azure environment (Azure cloud, DevOps, Azure Data Factory (ADF) using Python, Pyspark or Spark-SQL)
6-12 months of Vector Database experience comprising implementing databases like ChromaDB/Pinecone/FAISS, embedding, vectorization, performance tuning, indexing strategies, front-end integration, query optimization, efficient retrieval
Collaborate with application developers to integrate vector databases into various front-end UI solutions
Implement and maintain data security measures for vector databases
Ensure compliance with relevant data protection regulations and industry standards
Work closely with cross-functional teams, including data scientists, software engineers, and product managers
TECHNICAL SKILLS
Experienced in deploying data engineering solutions - database solutions, CI/CD pipelines, automated deployment/ testing
Proficient in data manipulation on Azure (Azure Cloud, Azure Data Factory) using Python, Pyspark, Spark-SQL, Java or Scala
Experienced in developing and implementing vector databases - ChromaDB/Pinecone/FAISS
Experienced with vector database concepts - embedding, vectorization, performance tuning, indexing strategies, front-end integration
Familiarity with AI, ML concepts - retrieval algorithms (RAG), NLP, LLM frameworks like Langchain
Knowledge of distributed database systems
CANDIDATE PROFILE
Bachelors/Master's degree in economics, mathematics, computer science/engineering, operations research or related analytics areas; candidates with BA/BS degrees in the same fields from the top tier academic institutions are also welcome to apply
Outstanding written and verbal communication skills
Superior analytical and problem-solving skills
Experience in working in dual shore engagement is preferred
Must have experience in managing clients directly
Strong record of achievement, solid analytical ability, and an entrepreneurial hands-on approach to work
LOCATION
Candidate can be based anywhere in US or Canada
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.