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Salary
≈ $72k – $183k per year (Estimated)
Location
Remote (Germany)

First seen by Alion on Apr 22, 2026. Salt scores C on the Alion truth index.

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Founded in 2009, Salt is a global digital talent, recruitment, and workforce consultancy specializing in technology, creative, marketing, and sales staffing. Headquartered in London, United Kingdom - with an international network of offices spanning North America, Europe, Asia-Pacific, and Latin America - the agency serves fast-scaling startups, mid-market companies, and multinational enterprises. Through its permanent and contract recruitment models, recruitment process outsourcing (RPO), nearshore/offshore talent delivery (Salt: Labs), and strategic HR advisory services, it enables organizations to build, scale, and manage high-performing teams across AI, technology, and digital transformation initiatives.

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AI Engineer / Data Scientist

Ref: JO-2604-360411

  • Environment:

    Remote

  • Contract Type:

    Contract

  • Starts:

    2026-05-11

Salt is currently hiring an AI engineer for a client of ours in Germany. The role is fully remote.

This project focuses on building a next-generation, AI-driven on-site search and product listing page (PLP) ranking capability. It requires specialized expertise in search relevance engineering, semantic and hybrid retrieval, multimodal embeddings, personalization, LLM-based query processing, and multilingual search systems.

The contractor provides niche expertise not available internally and delivers services independently.

Service Delivery Model

Work is delivered using a Scrum-based agile framework:

Two-week sprints with defined scope and priorities

Contractor proposes sprint deliverables based on independent assessment and expertise

Regular touchpoints (2-3 times per week) ensure alignment and transparency

The contractor operates autonomously, using their own methods and tools. All necessary access, documentation, and inputs are provided.

Scope of Services

Search Relevance Engineering: Configure and optimize OpenSearch components (analyzers, scoring, hybrid retrieval, vector search)

Retrieval & Ranking: Develop multi-stage ranking pipelines using relevance, behavioral, and business signals

Multilingual NLP: Implement locale-specific linguistic processing (tokenization, stemming, normalization)

Query Understanding: Build intent detection, synonym/concept expansion, and semantic query processing

LLM Integration: Incorporate LLM-based signals and prompt-engineered enhancements into search

Personalization: Develop re-ranking frameworks balancing user affinity, relevance, and commercial goals

Search UX Features: Deliver autocomplete, spell correction, and suggestion systems

*Rates depend on experience and client requirements

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