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Staff Applied ML Engineer

Machine Learning EngineerMachine Learning EngineerFull TimeRemoteLeadTeam 1,001-5,000H1B No SponsorCompany SiteLinkedIn

Location

Australia

Posted

47 days ago

Salary

0

Seniority

Lead

Bachelor Degree8 yrs expEnglishAWSCloudPython

Job Description

Staff Applied ML Engineer

Marigold

• Work across the Campaign Monitor product to identify valuable opportunities in product and customer data, and turn them into predictive features that improve customer outcomes • Turn rich historical product and customer data into predictive features that improve customer outcomes • Identify high-impact opportunities for applied machine learning by analyzing product, behavioral, and content data, and translating ambiguous product questions into concrete ML use cases • Develop and deploy predictive machine learning models, including models for click-through rate, churn, recommendations, and related engagement signals • Design and build features and training datasets from structured product data, historical behavioral data, and content-derived signals • Own the applied ML lifecycle from data exploration and feature engineering through training, evaluation, deployment, monitoring, and iteration • Build production services and workflows for batch and real-time inference, with a pragmatic focus on reliability, maintainability, and speed to impact • Work hands-on in the codebase, contributing to backend systems and product workflows that consume predictions and recommendations • Partner closely with product, design, and engineering to turn customer needs into ML-driven product capabilities with measurable business impact • Establish pragmatic best practices for model evaluation, experimentation, monitoring, and continuous improvement • Help shape how applied machine learning is introduced into the product, while aligning with broader engineering architecture and delivery practices • Contribute to shared knowledge across the engineering organization to improve understanding and adoption of applied ML over time.

Job Requirements

  • 7–8+ years building ML systems in production environments
  • Strong experience with applied machine learning for prediction, classification, regression, ranking, or recommendation problems
  • Experience with feature engineering, model evaluation, model lifecycle management, and production inference
  • Strong experience with Python and common ML tooling
  • Experience integrating ML systems into production products at scale
  • Strong understanding of backend systems, APIs, data pipelines, and scalable architecture
  • Experience with MLOps practices, including deployment, monitoring, retraining, and iteration
  • Experience with cloud platforms, preferably AWS.

Benefits

  • Remote-first, flexible hours
  • open time away (unlimited annual leave)
  • birthday leave
  • strong support for work-life harmony.
  • Regular team events
  • Devcamp
  • hackathons
  • Culture Club to build genuine relationships and celebrate together.
  • Clear career progression
  • mentorship
  • continuous learning opportunities
  • chance to work at scale on impactful projects.
  • Generous parental leave
  • home office setup allowance
  • salary continuance and life insurance
  • superannuation
  • access to Sydney office spaces.

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