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Staff ML Engineer

3 months, 2 weeks ago
New Zealand, Australia, United States
Full-time
Lead
Machine Learning Engineer
Software Development
Apache Spark AWS CI/CD Docker Feature Engineering Flink Go GraphQL Kubernetes Machine Learning Python React Ruby on Rails SQL
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Buildkite

Buildkite

Buildkite: Powerful CI/CD platform for fast, secure, and scalable pipelines on your own infrastructure, offering flexibility, security, and data-driven insights.

Commercial Services & Supplies
51-250
Founded 2014
$41M raised
View All Jobs 7

Description

  • Define and lead the ML strategy for predictive test selection from experimentation through production deployment.
  • Lead technical investigations into a generalized test selection model and adapt the approach based on data findings.
  • Design the end-to-end ML architecture, including feature engineering, model training, evaluation, serving infrastructure, and feedback loops.
  • Make key operational decisions around latency, accuracy trade-offs, and graceful degradation when confidence is low.
  • Integrate ML capabilities with Test Engine’s existing data infrastructure and test-to-code mapping systems.
  • Build and scale the ML platform layer so models can be shipped to production quickly and repeatably.
  • Design, build, and maintain data pipelines that connect code change signals with test execution history at scale.
  • Train, evaluate, deploy, monitor, and retrain ML models in production.
  • Instrument production models with observability metrics such as accuracy, latency, coverage, false negative rates, and drift detection.
  • Investigate and resolve complex performance and reliability issues across the data and ML stack.
  • Share engineering best practices through documentation, mentorship, and pairing.
  • Support cross-team tooling, infrastructure, and frameworks while aligning stakeholders on technical decisions.
  • Work closely with customers to understand their workflows and ensure test selection delivers real impact.

Requirements

  • Deep proficiency in Python and strong experience building production ML systems end-to-end.
  • Proven experience designing and operating ML infrastructure at scale, such as model registries, feature stores, serving layers, or experiment tracking.
  • Strong experience with large-scale data processing using batch or streaming frameworks such as Spark or Flink.
  • Deep proficiency in SQL.
  • Comfort working in AWS and with containerized workloads using Docker and Kubernetes.
  • Hands-on experience training, evaluating, and deploying ML models in production.
  • Experience with classification, ranking, or prediction problems with challenging signal-to-noise ratios.
  • Track record of building repeatable ML capabilities that scale beyond a single use case.
  • Experience with feature engineering from structured and semi-structured data such as code diffs, execution logs, or dependency graphs.
  • Experience instrumenting production models with observability metrics such as accuracy, latency, coverage, and drift.
  • Excellent written and verbal communication skills, especially in a remote-first environment.
  • Ability to explain complex technical concepts clearly to diverse audiences.
  • Collaborative, pragmatic mindset with the ability to balance technical quality and business context.
  • Comfort mentoring engineers and leading technical discussions across teams.
  • Proven ability to build alignment and influence technical direction without authority.
  • Experience with code analysis, static analysis tools, or features built from source code structure, preferred.
  • Familiarity with CI/CD systems, developer tooling, or test infrastructure, preferred.
  • Experience with Ruby on Rails, React, GraphQL, or Go, preferred.
  • Background in search ranking, recommendation systems, or similar sparse-signal domains, preferred.
  • Experience working with test frameworks or test execution data, preferred.

Benefits

  • Competitive compensation including salary, equity, and a benefits package.
  • Flexible, remote-first culture.
  • Remote work available in the ANZ and PST regions.
  • Opportunities for professional growth and technical leadership.
  • Cross-team influence on meaningful technical challenges at scale.
  • Collaborative, inclusive, and innovative culture.
  • Support for reasonable accommodations during the recruitment process.

Interested in this position?

Apply directly on the company website

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