Junior Search Relevance Engineer

TensorOps is a specialized consultancy dedicated to helping organizations accelerate their adoption of Artificial Intelligence and Machine Learning. We don’t just build models; we focus on MLOps, Cloud Engineering, and Generative AI, ensuring our clients can take their AI initiatives from experimental research to scalable production environments.

We partner with leading cloud providers (Google Cloud, AWS, Cloudflare) to solve complex infrastructure and engineering challenges. We are a team of engineers, architects, and innovators passionate about building the backbone of the next generation of AI.

"Are you feeling lucky?" 👀 We are looking for a Search Relevance Engineer to help us usher in the next era of internet search at TensorOps.

In recent months, we have been working with major high-traffic portals—sites visited by millions of users daily—to completely rethink how people navigate the web. Before Google, we navigated static directories. Today, no one imagines the web without intelligent search engines. What is happening now is the next step in that evolution.

Think about the shift from "ten blue links" to a conversational experience (like Perplexity) where users get contextual, personalized answers. We are making that happen for some of the world's largest publishers.

The days of visiting a major sports portal and receiving the exact same generic experience as everyone else are coming to an end. You will have the privilege of helping these publishers transition into a world of hyper-relevance. If you want to move beyond simple keyword matching and work on the features that define the modern search experience, this is the place to be.

• Re-Engineering Search: Design and implement search strategies that combine traditional lexical search (BM25) with semantic vector search (Embeddings) to improve result quality.

• RAG Implementation: Build and optimize Retrieval-Augmented Generation (RAG) pipelines that allow LLMs to "chat" with proprietary data accurately.

• Relevance Tuning: Measure and improve search metrics (NDCG, MAP, MRR). You will analyze why a user didn't find what they were looking for and fix the ranking logic.

• Pipeline Engineering: Collaborate with Data Engineers to ensure indexing pipelines are efficient, scalable, and real-time.

• Personalization: Develop logic that tailors search results based on user intent and context, moving away from "one-size-fits-all" query results.

• Client Collaboration: Work closely with technical teams from our client partners to understand their data structures and business goals.

• Experience: 1-2 years of experience in Software Engineering, Data Engineering, or Data Science with a focus on Search or NLP.

• Core Tech: Strong proficiency in Python.

• Search Engines: Hands-on experience with at least one major search technology (Elasticsearch, OpenSearch, Solr) or Vector Databases (Pinecone, Weaviate, Milvus, Qdrant).

• Understanding of NLP: You understand concepts like Tokenization, Embeddings, and Named Entity Recognition (NER).

• Data Fluency: You are comfortable working with SQL and data processing frameworks.

• Communication: Native/Fluent level English is mandatory. You must be able to explain complex ranking logic to non-technical stakeholders.

• Location: Based in Lisbon/Portugal (we are remote-first, but team cohesion in our hub is important).

• Experience building RAG (Retrieval Augmented Generation) systems in production.

• Familiarity with Learning to Rank (LTR) algorithms (XGBoost for ranking, etc.).

• Experience with LangChain or LlamaIndex.

• Knowledge of Cloud Infrastructure (AWS, GCP) and containerization (Docker/Kubernetes).

• A background in working with high-traffic media or e-commerce platforms.

Build the Future. Work from Anywhere. We are a remote-first company that values autonomy, mastery, and purpose. At TensorOps, you aren't just a number; you are part of a tight-knit team of experts solving some of the hardest problems in the industry.

We believe in flexible work schedules that allow you to balance your professional ambitions with your personal life. We support continuous learning, speaking at conferences, and contributing to the open-source community.

Join us in productionizing the world of AI.