Information Retrieval Engineer

Mercor is hiring an Information Retrieval Engineer on behalf of a leading AI lab. In this role, you’ll design indexing, ranking, and evaluation pipelines that combine traditional IR methods with neural re-rankers. You’ll build scalable, low-latency search systems capable of serving massive text corpora with high relevance and reliability. This position is ideal for engineers passionate about search, large-scale systems, and the intersection of IR and machine learning.

You’re a great fit if you:

• Have a background in computer science, information retrieval, or data engineering.

• Are proficient with Elasticsearch/OpenSearch for indexing and querying large text stores.

• Have experience with neural search and reranking using FAISS, Hugging Face, and PyTorch.

• Understand traditional IR methods such as BM25 and TF-IDF and how to integrate them with modern ML approaches.

• Can design low-latency pipelines that serve results efficiently at scale.

• Are comfortable working with pandas for data analysis and building evaluation workflows.

• Have experience integrating pipelines into systems via REST APIs.

Primary Goal of This Role

To design and implement hybrid IR systems that blend traditional retrieval methods with neural re-rankers, enabling scalable, low-latency, and highly relevant search across massive text datasets.

What You’ll Do

• Build and optimize indexing and ranking pipelines using Elasticsearch/OpenSearch and FAISS.

• Develop neural re-rankers with Hugging Face Transformers and PyTorch.

• Combine BM25, TF-IDF, and neural models into hybrid search frameworks.

• Design and implement evaluation pipelines to benchmark retrieval performance.

• Optimize systems for low-latency performance at scale.

• Collaborate with researchers and engineers to integrate IR pipelines into production AI systems.

Why This Role Is Exciting

• You’ll shape the next generation of search and retrieval systems.

• You’ll apply both traditional IR methods and state-of-the-art neural re-rankers.

• You’ll work on massive-scale text datasets with real-world impact.

• You’ll operate at the intersection of search, machine learning, and large-scale systems engineering.

Pay & Work Structure

• Weekly Bonus of $500–$1000 USD per 5 tasks.

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.

Contract and Payment Terms

• You will be engaged as an independent contractor.
• This is a fully remote role that can be completed on your own schedule.
• Projects can be extended, shortened, or concluded early depending on needs and performance.
• Your work at Mercor will not involve access to confidential or proprietary information from any employer, client, or institution.
• Payments are weekly on Stripe or Wise based on services rendered.
• Please note: We are unable to support H1-B or STEM OPT candidates at this time.

About Mercor

Mercor partners with leading AI labs and enterprises to train frontier models using human expertise. You will work on projects that focus on training and enhancing AI systems. You will be paid competitively, collaborate with leading researchers, and help shape the next generation of AI systems in your area of expertise.