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DIMP 模型工程师

DIMP Model Engineer

开发工程限定地区(需当地身份)
公司Irth
薪资未公开
工作地点Canada
地域资格限定地区(需当地身份)
时区要求日间重叠约 6 小时,基本正常作息
用工类型Full Time
发布时间今天
数据来源Himalayas
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注意地域限制:该职位明确限定在 Canada 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

风险模型工程师 — 燃气分布完整性
地点:远程(美国或加拿大)
部门:洞察(AI/ML)
汇报对象:数据科学团队负责人
职位简介
Irth 正在构建一个全新的基于 AI 的威胁和风险管理系统,用于管道资产的完整性。该平台整合了三种此前在 Irth 从未集中在一起的能力:

  • 基于 Databricks 和 Azure 构建的受控、跨产品的数据平台。
  • 一种由 AI 驱动的数据摄入层,可在无需大量服务支持的情况下对客户数据进行标准化、修复和增强。
  • 一个可重复使用的分析层,可在这些数据上运行行业标准、Irth 自研以及客户自建的风险模型。

我们正在招聘一名风险模型工程师,负责该分析层中的燃气分布风险模型。
分布是一个新的模型领域,威胁框架和模型集目前正在与领域专家和设计合作伙伴操作人员合作定义。在此职位上,您将帮助定义模型、构建模型,并通过验证——生成可用于优先排序更换计划和支持监管程序的输出。
建模工作聚焦于大量埋地资产,这些资产的已观测故障较少,记录不完整,直接检查数据有限。这项工作涵盖基于物理的概率模型和机器学习,重点是生成可解释、校准和可辩护的风险排名。
您将负责模型内容:模型计算什么、为什么计算它,以及支持其有效性的证据。
生产化——包括模型服务、数据流水线、部署和监控基础设施——由专门的 ML Ops 和数据工程角色负责,您将与他们密切合作。
主要职责
1. 威胁框架与集成

  • 与领域专家合作,将燃气分布威胁框架转化为系统化的威胁识别方法和支撑的数据结构。
  • 整合来自 Irth 产品线中各种数据集的模型输入。
  • 识别源数据中的差距、不一致和限制,并确定它们应如何体现在模型输入和输出中。

2. 模型开发

  • 扩展威胁覆盖范围,包括:
  • 老旧材料腐蚀
  • 塑料脆化
  • 开挖损坏
  • 交叉孔
  • 其他燃气分布相关问题
  • 要求
  • 我们正在招聘的技能
查看英文原文

Risk Model Engineer — Gas Distribution Integrity
Location: Remote (US or Canada)
Department: Insights (AI/ML)
Reports to: Data Science Team Lead
About the Role
Irth is building a new AI-driven threat and risk management platform for pipeline asset integrity. The platform brings together three capabilities that have never previously lived in one place at Irth:

  • A governed, cross-product data platform built on Databricks and Azure.
  • An AI-powered ingestion layer that normalizes, repairs, and enriches customer data without services-heavy onboarding.
  • A reusable analytical layer that runs industry-standard, Irth-developed, and customer-built risk models against that data.

We are hiring a Risk Model Engineer to own the gas distribution risk models within that analytical layer.
Distribution is a new model domain for the platform. The threat framework and model set are being defined now in collaboration with subject-matter experts and design-partner operators. In this role, you will help define the models, build them, and take them through validation—producing outputs that utilities can use to prioritize replacement programs and support regulatory proceedings.
The modeling work focuses on large populations of buried assets with relatively few observed failures, incomplete records, and limited direct inspection data. The work spans physics-based probabilistic models and machine learning, with an emphasis on producing risk rankings that remain explainable, calibrated, and defensible.
You will own the model content: what the model computes, why it computes it, and the evidence supporting its validity.
Productionization—including model serving, data pipelines, deployment, and monitoring infrastructure—is owned by dedicated ML Ops and data engineering roles with whom you will work closely.
Key Responsibilities
1. Threat Framework & Integration

  • Translate the gas distribution threat framework, in collaboration with subject-matter experts, into systematic threat identification methods and supporting data structures.
  • Integrate model inputs from diverse datasets across Irth's product offerings.
  • Identify gaps, inconsistencies, and limitations in source data and determine how they should be reflected in model inputs and outputs.

2. Model Development

  • Extend threat coverage across domains, including:
  • Legacy material corrosion
  • Plastic embrittlement
  • Excavation damage
  • Cross-bores
  • Other gas distribution

Requirements
Skills We're Hiring For
We are hiring across a broad range of capabilities and do not expect a single candidate to have all of them. We are looking for strong depth in one or more areas and the curiosity and judgment to work across the others.
Relevant experience may include:

  • Gas distribution integrity management — program design, threat identification under 49 CFR Part 192, Subpart P, and replacement prioritization, from the operator, consultancy, regulator, or technology-vendor side.
  • Legacy material risk — cast iron, bare steel, vintage plastics, and plastic embrittlement.
  • Leak survey, methane detection, and cross-bore programs.
  • Machine learning applied to physical asset data, including time-series, survival, anomaly-detection, and classification models trainer

Benefits
Benefits

  • Competitive Salary – A competitive compensation package based on experience and qualifications.
  • Medical, Dental, and Vision Insurance – Comprehensive insurance coverage to support you and your family.
  • 401(k) Plan with Company Match.
  • Generous Paid Time Off (PTO) – Time off to support work-life balance and personal needs.
  • Company-Paid Holidays – Paid holidays throughout the year.
  • Flexible Work Options – Work-from-home opportunities are available, depending on role and business needs.
  • On-Call Compensation – Additional pay for eligible on-call shifts.

Originally posted on Himalayas

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