Member of Technical Staff
Build and deploy retrieval, ranking, classification, and LLM-based systems that improve large-scale search quality. The role requires deep search or recommender-systems expertise and at least five years of relevant project experience.
About the job
Responsibilities
- Push search quality forward through models, data, tools, and other leverage.
- Architect and build core components of the search platform and model stack.
- Train and evaluate retrieval, ranking, and classification models, including large language models (LLMs).
- Deploy models—from boosting to LLMs—in a scalable and performant way.
- Build and optimize retrieval-augmented generation (RAG) pipelines for grounding and answer generation.
- Collaborate with Data, AI, Infrastructure, and Product teams to deliver quickly and with high quality.
Requirements
- Deep understanding of search and retrieval systems, including quality evaluation principles and metrics.
- Proven track record with large-scale search or recommender systems.
- Self-driven, with a strong sense of ownership and execution.
- Minimum of 5 years working on search- or recommender-system-related projects.
Skills
Machine Learning, Search Systems, Information Retrieval, Recommender Systems, Ranking Models, Classification Models, LLMs, RAG, Model Deployment, Python
Similar jobs
ML Engineering jobs
Rollstack
United StatesBuild production AI capabilities for automated slide and document generation, working across LLM applications, data analysis, and content generation. The role requires 3+ years in machine learning and NLP, advanced Python, and experience with LLM frameworks and production systems.
OpenAI
London, United Kingdom
Build and deploy AI-powered products for digital-native customers, taking systems from experimentation through production and scale. The role requires strong Python skills, hands-on production engineering, systematic AI evaluation, and the ability to navigate reliability, security, governance, and customer impact.
Elliptic
London, United Kingdom
Build full-stack AI agent fleets, APIs, workflows, and internal services that automate complex business processes. The role requires at least five years of engineering experience, hands-on LLM framework experience, production AWS expertise, Kubernetes, and strong API and database skills.
Protege
Remote
Build the technical foundation for a new business vertical, creating reusable infrastructure and leading early customer engagements from scoping through delivery. The role requires 3+ years of engineering experience, strong Python and SQL skills, backend/data expertise, and comfort operating in ambiguity.
DeepIntent
Belgrade, Serbia
Build and operate scalable MLOps infrastructure for distributed training and inference across on-premises and GPU environments. The role partners with data science and AI teams and requires production experience with Python, Spark, Docker, Kubernetes, and open-source MLOps tooling.