Senior Machine Learning Engineer

Capital6, LLC
New York, NY, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Data Mining Distributed Systems Graph Database Information Extraction Python (Programming Language) Machine Learning Natural Language Processing Parsing Recommender Systems Software Engineering Large Language Models
+8 more
Multi-Agent Systems Deep Learning Indexer AI Platforms Kubernetes Production Code Data Analytics Machine Learning Operations

Job description

We’re looking for a Senior II Machine Learning Engineer to help shape the future of AI in construction. You’ll join a fast-growing technology company using advanced machine learning, large language models and intelligent automation to solve complex, real-world challenges across a multi-trillion-pound global industry. This is an opportunity to work on production AI systems at scale, collaborating with a highly experienced engineering team to build products that have a measurable impact on how major construction projects are delivered. What you’ll be doing

  • Own and develop key components of our AI platform, including search, retrieval and multi-agent orchestration.
  • Lead the design and implementation of multi-agent architectures, defining how specialist agents interact to solve complex tasks.
  • Design, build and optimise large-scale document processing pipelines, covering ingestion, parsing, chunking, indexing and structured data extraction.
  • Improve search and retrieval capabilities through ranking, query understanding and AI-powered question answering based on real customer needs.
  • Expand and maintain knowledge graph capabilities, modelling relationships between entities to improve reasoning and retrieval.
  • Take ownership of high-impact projects from concept through to production, balancing experimentation with practical delivery.
  • Develop evaluation frameworks and experimentation processes to measure model performance and continuously improve quality.
  • Write clean, scalable, production-ready code while promoting engineering best practices across the team.

Requirements

We’re looking for someone who enjoys solving difficult engineering problems and turning research into reliable production systems. You’ll ideally have:

  • 7+ years’ experience designing, building and deploying production-grade machine learning or AI systems.
  • A proven ability to lead technically challenging projects with significant business impact.
  • Strong experience building LLM-powered applications, AI agents or orchestration frameworks.
  • Deep knowledge of document processing pipelines, including parsing, chunking, indexing and structured information extraction.
  • Experience working with distributed systems such as Kubernetes.
  • Knowledge of knowledge graphs, provenance graphs or similar graph-based data models.

Experience in one or more of the following areas:

  • Search and ranking systems
  • Natural Language Processing (NLP)
  • Recommendation systems
  • Large-scale ML infrastructure
  • Strong software engineering skills in Python, Go or similar languages.
  • An analytical mindset with a strong focus on delivering value through data-driven decisions.

Nice to have

  • Experience working within construction, engineering or other document-intensive industries.

Benefits & conditions

  • Competitive salary with equity options.
  • Comprehensive medical, dental and vision cover.
  • Learning and professional development budget.
  • Flexible remote and hybrid working arrangements.
  • Unlimited annual leave because we value sustainable, long-term performance.
  • Regular company meet-ups and team retreats.
  • A collaborative environment where your ideas genuinely influence the direction of the product and engineering organisation.

If you’re passionate about building production AI systems, enjoy working on technically demanding problems and want to help redefine how a global industry operates, we’d love to hear from you.

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