出海雷达

资深机器学习平台工程师

Staff ML Platform Engineer

AI开发工程限定地区(需当地身份)
公司Datavant
薪资$224,000 - $280,000/年
工作地点United States
地域资格限定地区(需当地身份)
时区要求日间重叠约 9 小时,基本正常作息
用工类型Full Time
发布时间15 天前
数据来源Himalayas
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注意地域限制:该职位明确限定在 United States 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。

Datavant 是医疗保健领域值得信赖的数据协作平台。我们致力于让世界上的健康数据更加安全、可访问和可操作,为整个医疗生态系统中的组织提供关键的数据解决方案——包括医疗机构、健康计划公司、研究人员和生命科学公司。从满足一位患者获取病历的请求,到推动医疗领域的 AI 革命,Datavant 的员工正在构建数据如何连接和用于改善健康的未来。

加入 Datavant,你将加入一个充满激情且高度协作的团队,他们致力于在医疗领域创造变革性的影响。

我们寻找的人选
我们正在寻找一名资深机器学习平台工程师加入我们的数据与机器学习平台组织的机器学习平台团队。我们负责一条“铺好的道路”,使模型可以从笔记本直接部署到生产环境而无需每次重新构建:跨 SageMaker 和 Databricks 的训练和推理、自助式大语言模型端点服务,以及 Datavant 临床 AI 产品背后的流水线。数据科学团队负责模型及其质量;我们负责流水线、服务基础设施和运营保障措施,使这些模型能够在受监管的健康数据上安全运行。
作为资深机器学习平台工程师,你将在机器学习平台中担任技术领导者:设定“铺好的道路”的方向,负责最复杂的架构问题,并带领团队从定制化管道转向一个统一的平台,供数据科学团队自助使用。对 AI 的熟悉是基本要求。你应该已经将 Claude Code、Cursor、Copilot 或类似工具作为日常工程工作流程的核心部分,对它们如何提升团队效率有见解,并知道在涉及 PHI 和其他敏感数据时如何负责任地应用它们。
你将负责的工作

  • 设定机器学习训练、服务和可观测性的技术方向,并成为解决最棘手基础设施问题(GPU 资源、Spark 调优、生产事件)的最终责任人
  • 主导并演进我们的“铺好的道路”框架(共享的 CI/CD 骨干、模型工作流模板和 Databricks 资产包),使数据科学团队能够从配置文件直接进入生产工作流,而无需定制化管道
  • 主导跨托管供应商(Databricks、AWS、Snowflake)和自托管部署的大语言模型端点服务架构,涵盖延迟、成本、缓存、评估和 PHI 安全路由
  • 负责标准
查看英文原文

Datavant is the data collaboration platform trusted for healthcare. Guided by our mission to make the world’s health data secure, accessible and actionable, we provide critical data solutions for organizations across the healthcare ecosystem - including providers, health plans, researchers, and life sciences companies. From fulfilling a single patient’s request for their medical records to powering the AI revolution in healthcare, Datavanters are building the future of how data is connected and used to improve health.

By joining Datavant today, you’re stepping onto a driven and highly collaborative team that is passionate about creating transformative change in healthcare.

What We’re Looking For
We are looking for a Staff ML Platform Engineer to join our Data & ML Platform organization on the ML Platform team. We own the paved road that takes a model from notebook to production without rebuilding it each time: training and inference across SageMaker and Databricks, self-service LLM-endpoint serving, and the pipelines behind Datavant’s clinical-AI products. Data Science owns the models and their quality; we own the pipelines, serving infrastructure, and operational guardrails that let those models run safely against regulated health data.
As a Staff ML Platform Engineer, you will be a technical leader across the ML Platform: setting direction for the paved road, owning the hardest architectural problems, and moving the team from bespoke plumbing toward a coherent platform that Data Science teams can self-serve. AI fluency is a baseline expectation. You should already be using Claude Code, Cursor, Copilot, or equivalent tools as a core part of your daily engineering workflow, have opinions about how they make a team faster, and know how to apply them responsibly when PHI and other sensitive data are in scope.
What You Will Do

  • Set technical direction across ML training, serving, and observability, and be the final escalation point for the most elusive infrastructure problems (GPU capacity, Spark tuning, production incidents)
  • Own and evolve our paved-road framework (the shared CI/CD spine, model-workflow scaffolding, and Databricks Asset Bundles) so Data Science teams can go from a config file to a production workflow without bespoke plumbing
  • Lead architecture for LLM-endpoint serving across managed providers (Databricks, AWS, Snowflake) and self-hosted deployments, covering latency, cost, caching, evaluation, and PHI-safe routing
  • Own the standards and tooling for MLflow, model registry, training image supply chain, and observability across training and inference
  • Partner closely with your Data & ML Platform teammates to present a cohesive ML platform to the Data Science, App Dev, and Operations teams at Datavant
  • Serve as a key technical input to vendor and platform selection decisions across model providers, ML tooling, and observability
  • Mentor senior engineers on the team, provide technical guidance to platform consumers, and stay hands-on writing high-leverage code and Infrastructure-as-Code alongside your teammates

What You Need to Succeed

  • 10+ years of software engineering experience, with 3+ years designing, evolving, and operating enterprise-scale ML platforms in production
  • Strong technical judgment under ambiguity and a track record of setting standards, influencing peers, and raising the bar across teams
  • Hands-on production experience with Databricks and/or Amazon SageMaker, MLflow (or an equivalent tracking + registry system), and at least one core ML framework (PyTorch, TensorFlow, or similar)
  • Fluency in Java (or a JVM equivalent) and Python, with real depth in Apache Spark for large-scale data and distributed compute
  • Real depth in AWS: networking, IAM, GPU compute, and the storage and messaging services this role touches, with the judgment to know what to reach for and when
  • Fluency with Terraform, containers, Kubernetes, and GitHub-based CI/CD for ML workloads
  • Direct experience serving LLMs in production, including cost management, evaluation harnesses, and safe handling of sensitive prompts and outputs
  • AI-native working style: daily use of Claude Code, Cursor, Copilot, or equivalent, with views on how they make a team faster
  • Clear written and verbal communication, especially in async, remote settings

What Helps You Stand Out

  • Prior technical leadership on a healthcare or regulated-industry ML platform (HIPAA, HITRUST, SOC 2, or equivalent)
  • Direct experience with Databricks Asset Bundles, Unity Catalog, and open table formats (Iceberg, Delta)
  • Production experience with specialized inference pipelines beyond generic model serving (e.g., document understanding, computer vision, or streaming inference)
  • GPU capacity planning at strategic, tactical, and operational horizons
  • Experience with real-time and event-driven inference and streaming platforms (Kafka, Kinesis)
  • Evaluation and red-teaming experience for clinical or safety-sensitive AI
  • Background contributing to open-source ML infrastructure or publishing on production ML systems

We are committed to building a diverse team of Datavanters who are all responsible for stewarding a high-performance culture in which all Datavanters belong and thrive. We are proud to be an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status.

At Datavant our total rewards strategy powers a high-growth, high-performance, health technology company that rewards our employees for transforming health care through creating industry-defining data logistics products and services.

The range posted is for a given job title, which can include multiple levels. Individual rates for the same job title may differ based on their level, responsibilities, skills, and experience for a specific job.

The estimated total cash compensation range for this role is:

$224,000—$280,000 USD

To ensure the safety of patients and staff, many of our clients require post-offer health screenings and proof and/or completion of various vaccinations such as the flu shot, Tdap, COVID-19, etc. Any requests to be exempted from these requirements will be reviewed by Datavant Human Resources and determined on a case-by-case basis. Depending on the state in which you will be working, exemptions may be available on the basis of disability, medical contraindications to the vaccine or any of its components, pregnancy or pregnancy-related medical conditions, and/or religion.

This job is not eligible for employment sponsorship.

Datavant is committed to a work environment free from job discrimination. We are proud to be an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status. To learn more about our commitment, please review our EEO Commitment Statement here. Know Your Rights, explore the resources available through the EEOC for more information regarding your legal rights and protections. In addition, Datavant does not and will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay.

At the end of this application, you will find a set of voluntary demographic questions. If you choose to respond, your answers will be anonymous and will help us identify areas for improvement in our recruitment process. (We can only see aggregate responses, not individual ones. In fact, we aren’t even able to see whether you’ve responded.) Responding is entirely optional and will not affect your application or hiring process in any way.

Datavant is committed to working with and providing reasonable accommodations to individuals with physical and mental disabilities. If you need an accommodation while seeking employment, please request it here, by selecting the ‘Interview Accommodation Request’ category. You will need your requisition ID when submitting your request, you can find instructions for locating it here. Requests for reasonable accommodations will be reviewed on a case-by-case basis.

For more information about how we collect and use your data, please review our Privacy Policy.

Originally posted on Himalayas

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