Vector Database Engineer Job at Bright Vision Technologies

Staff Software Engineer, Database Systems

Zilliz is a fast-growing startup developing the industry’s leading vector databa...

Location

Salary:

175000.00 - 250000.00 USD / Year

Zilliz

Expiration Date

Until further notice

Requirements

4+ years of experience in developing database systems
Active contributor to one or more infrastructure software such as Snowflake, CockroachDB, Oracle RDBMS, Google BigQuery, Spanner, Redshift, Aurora, Cosmos DB, MySQL, PostgreSQL, Hudi, Delta Lake, Iceberg, Ray, Spark, Flink, Kafka, Redis, ElasticSearch, etc.
Bachelor’s degree or above in computer science, software engineering, or other relevant disciplines
Willing to adapt to a fast-changing environment (i.e. the different stages of a startup company)

Job Responsibility

Develop distributed database systems using Zilliz’s innovative data science platforms
Create request plans, develop new systems, and perform prototype verification and testing
Design and write core architecture code
Provide creative solutions to technical issues that arise during the product development process
Take ownership of product performance and stability
Research emerging technology to optimize the performance of underlying distributed platforms
Manage the Milvus open-source community and broaden Zilliz’s reach worldwide

What we offer

Competitive compensation (cash + equity)
Regular bonus and equity refresh opportunities
Medical, dental, and vision insurance
Paid time off, including vacation, sick leave, and global reset/wellbeing days
Generous 401(k) and regional retirement plans

Fulltime

ML and Search Engineer, RAG and Re-ranking

The ML and Search Engineer, RAG and Re-ranking will focus on designing and optim...

Location

Salary:

Not provided

ACI Infotech

Expiration Date

Until further notice

Requirements

Degree in Computer Science, ML, IR, or related discipline
Strong background in information retrieval and machine learning (embeddings, search ranking)
Hands-on experience with vector databases (pgvector, Pinecone, Qdrant)
Skilled in Python ML stack including PyTorch and Hugging Face
Practical experience tuning retrieval pipelines for quality and latency
Experience shipping search or RAG features to production
Clear understanding of retrieval metrics (NDCG, MRR) and experiment design

Job Responsibility

Design and optimize RAG pipelines including chunking, embeddings, and retrieval
Build and deploy re-ranking models and hybrid search strategies
Create evaluation datasets and metrics for offline and online testing
Collaborate with product and data teams to drive measurable quality improvements in production
Ensure higher NDCG and MRR with defined quality and latency SLOs
Develop robust evaluation harnesses and experiment frameworks

Fulltime

AI Engineer

Prolific is not just another player in the AI space – we are the architects of t...

Location

United Kingdom

Salary:

Not provided

Prolific

Expiration Date

Until further notice

Requirements

A strong track record of designing, building, and shipping AI-powered features that have solved real business problems
An inquisitive and experimental mindset, with a passion for tackling ambiguous problems that may not have established solutions
Deep practical knowledge of the modern AI engineering stack (e.g., RAG, vector databases, prompt engineering, fine-tuning techniques, and evaluation frameworks)
The ability to thoughtfully balance cutting-edge research with the practical constraints of production reliability and scalability
Deep expertise in one, or both of the following areas: Software Engineering & Systems Design: Expertise in Python and experience building scalable services (e.g., using FastAPI, Django). You have a strong command of system design, infrastructure, and CI/CD pipelines, and you're comfortable taking a feature from concept to deployment
Machine Learning Engineering & Research: A comprehensive background in machine learning, with deep experience in ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and a strong grasp of the underlying theory behind the models and techniques you use

Job Responsibility

Architect & Build: Lead the design and implementation of production-grade AI systems that enhance how human feedback is collected, validated, and utilised across our platform
Solve Core Challenges: Develop sophisticated systems for fraud detection, quality assurance, and intelligent participant-to-task matching using techniques like vector search and advanced profile representation
Innovate with LLMs: Create and deploy AI agents and systems with immediate product impact - from basic automated data tagging, to advanced features like LLM-based evaluation judges, all the way to experimental ideas such as synthetic personas
Drive Technical Strategy: Provide technical leadership and mentorship on the practical application of AI/LLM techniques, defining best practices for everything from prompt engineering to fine-tuning and RAG
Ensure Reliability: Implement and own LLM observability and evaluation systems to ensure our AI features are reliable, performant, and continuously improving
Collaborate Cross-Functionally: Work closely with data scientists, platform engineers, and research teams to build cohesive, end-to-end solutions that push the boundaries of human-AI interaction

What we offer

competitive salary
benefits
remote working
impactful, mission-driven culture

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