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Est. Monthly
Estimated €5,500 - €7,000
Posted August 6, 2026 · 2 days agoLast seen August 7, 2026Est. expiry September 10, 2026

Software Engineer

Senior Software Engineer (Search / Retrieval)
Palo Alto, United States
Hybrid · Software Engineering
Full-time · Senior
English
No People Management
Bachelor
7 years experience
How this salary compares
Salary Context: Software Engineer

Hover or tap a row for full statistics (EUR / month on this chart).

Salary analysis

Compared with the selected benchmark ("Market Average: Senior Level"), this listing's salary midpoint is about 94% lower. The offer sits below the benchmark range (€5,000–€12,622). The listed pay band (€458–€583) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 53 comparable listings.

Monthly salary comparison for Software Engineer
MarketLower bound (25th percentile)MedianUpper bound (75th percentile)
Market Average: Software Engineer€3,500/per month€5,750/per month€12,307/per month
Pay in our data — not quoted in ad (Senior)€458/per month€521/per month€583/per month
About the role

We are looking for an exceptional Senior Software Engineer (Search / Retrieval) to join our growing team. In this role, you will lead the design, development, and optimization of intelligent search systems that leverage machine learning at their core. Youll be responsible for building end-to-end retrieval pipelines that incorporate advanced techniques in query understanding, ranking, and entity recognition. The ideal candidate combines deep expertise in information retrieval and search relevance with hands-on experience applying machine learning to real-world search problems at scale. Responsibilities: - Lead the development of advanced our search cluster that can scale to millions of documents across customers and data sources - Deploy learning-to-rank models that optimize relevance using behavioral signals, embeddings, and structured feedback. - Build and scale robust Entity Recognition pipelines that enhance document understanding, enable contextual disambiguation, and support entity-aware retrieval. - Architect next-gen search infrastructure capable of supporting highly dynamic document corpora and real-time indexing. - Drive improvements in query construction, indexing and search performance - Be up-to-date with the latest improvements in search and indexing technologies - Collaborate with product and applied research teams to translate user needs into data-informed search innovations - Produce clean, scalable code and influence system architecture and roadmap across the relevance and platform stack. Requirements: - Bachelors/Masters/PhD degree in Statistics, Mathematics or Computer Science, or another quantitative field. - 7+ years of backend engineering experience with 3+ years in search, information retrieval, or related fields - Strong proficiency in Python - Hands-on experience with search engines (Opensearch or Elasticsearch) - Strong understanding of information retrieval concepts spanning traditional methods (TF-IDF, BM25) and modern neural search techniques (vector embeddings, transformer models) - Experience with text processing, NLP, and relevance tuning - Experience with relevance evaluation metrics (NDCG, MRR, MAP) - Experience with large-scale distributed systems - Strong analytical and problem-solving skills Soft Skills: - Strong communication abilities to explain technical concepts - Collaborative mindset for cross-functional team work - Detail-oriented with strong focus on quality - Self-motivated and able to work independently - Passion for solving complex search problems

Job Details

Responsibilities

  • Lead the development of search clusters scaling to millions of documents
  • Deploy learning-to-rank models using behavioral signals, embeddings, and structured feedback
  • Build and scale Entity Recognition pipelines for document understanding and entity-aware retrieval
  • Architect next-gen search infrastructure for dynamic document corpora and real-time indexing
  • Improve query construction, indexing, and search performance
  • Stay current with search and indexing technology improvements
  • Collaborate with product and research teams to implement search innovations
  • Produce clean, scalable code and influence system architecture and roadmap

Requirements

  • Bachelors/Masters/PhD degree in Statistics, Mathematics, Computer Science, or another quantitative field
  • 7+ years of backend engineering experience
  • 3+ years of experience in search, information retrieval, or related fields
  • Strong proficiency in Python
  • Hands-on experience with Opensearch or Elasticsearch
  • Understanding of traditional IR methods (TF-IDF, BM25) and neural search (vector embeddings, transformer models)
  • Experience with text processing, NLP, and relevance tuning
  • Experience with relevance evaluation metrics (NDCG, MRR, MAP)
  • Experience with large-scale distributed systems
  • Strong analytical and problem-solving skills
  • Strong communication abilities to explain technical concepts
  • Collaborative mindset for cross-functional team work
  • Detail-oriented with strong focus on quality
  • Self-motivated and able to work independently

Skills & Technologies

PythonOpenSearchElasticsearchTF-IDFBM25Vector EmbeddingsTransformer ModelsNLPNDCGMRRMAPDistributed Systems

Education Level

Bachelor
Seen 23 hours agoContent Complete
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