AI/ML Engineer

Job not on LinkedIn

🕒 July 9

🇬🇧 United Kingdom – Remote

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 24%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Future Works

WebsiteLinkedInAll Job Openings

11 - 50 employees

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Future Works is a company that specializes in providing digital transformation solutions for industries looking to enhance their business operations using AI-driven technology and custom software. They focus on a range of sectors including real estate, aerospace, energy and climate, delivering innovative solutions that aim to modernize systems, streamline operations, and improve market positions. Future Works offers next-generation digital transformation, innovation and R&D services, and strategic branding. They pride themselves on their proprietary expertise and a strong blend of technology and design. Their services empower companies to succeed in a rapidly evolving technological landscape.

📋 Description

• Per-Stage Agent Build: Implement agent capabilities for individual workflow stages (for example engagement agreement generation, needs-assessment brief, market survey and long-list scoring, tour management, RFP and proposal analytics, lease abstraction, and close-out and invoicing), building to the orchestration model and stage handoff protocols defined by the Lead Architect. • Tool & Integration Development: Build the typed tools the agents call: template population, market-data query, financial analytics (NER, TI, free rent, NPV), clause and lease-clause extraction, and document assembly. • Data Pipelines: Build and maintain pipelines against sandbox and representative sample data, including the property availability data source. • Human-in-the-Loop Implementation: Encode the approval gates and review checkpoints specified by the architect, so binding steps always route through a broker confirmation. • Quality & End-to-End Testing: Validate components against deal-scenario data and participate in end-to-end testing across all eight stages, checking artifact quality and stage handoff integrity. • Build-Phase Readiness: Participate in Phase 1 architecture workshops to ensure the build starts on solid foundations.

🎯 Requirements

• 4+ years in software or machine learning engineering, with production experience building LLM-powered features or agents. • Agent Tooling: Hands-on experience with agent frameworks, tool and function calling, retrieval, and prompt engineering. • Python & Data Engineering: Strong Python and practical experience building data pipelines and integrating structured and unstructured data sources. • Document Processing: Comfort parsing, extracting, and generating documents across formats such as PDF, DOCX, and structured templates. • Financial & NLP Depth: Experience implementing financial analytics (lease economics, NPV, scenario modelling) and NLP information extraction (clause and entity extraction from contracts or leases) is strongly preferred. • Domain Exposure: Exposure to commercial real estate or another document-heavy transaction domain is a plus. • AI-Native Workflow: Comfort utilizing LLM code assistants and agentic engineering to ship faster and with higher quality. • Agile Execution: Ability to move quickly in hypothesis-driven, milestone-based sprint cycles, shipping working components and iterating against real evidence.

🏖️ Benefits

• Work from anywhere, forever - We are a fully remote and global team. We trust you to manage your time and energy to deliver exceptional results. • Connect deeply - We gather for immersive, all-expenses-paid company retreats in unique locations to connect, learn, and grow together. • Share in the upside - A competitive compensation package including equity, bonuses, substantial participation in company profits with a clear growth path to C-Level leadership based on performance.