Senior Machine Learning Engineer

Role Summary

We are seeking an experienced Senior Machine Learning Engineer to lead the end-to-end lifecycle of machine learning models—from their design and training phases through to deployment at production scale. This is a full-time remote position based in Australia, offering a competitive salary package aligned with experience and qualifications.

Key Responsibilities

• Architect, develop, and deploy machine learning models for production environments.
• Make informed decisions regarding the design of training, evaluation, and inference pipelines.
• Create frameworks to evaluate model performance and implement monitoring to detect model quality degradation and data drift.
• Collaborate with data engineering teams on data pipelines and feature store integrations.
• Mentor and guide junior machine learning engineers and actively contribute to the growth of ML best practices within the team.
• Keep up to date with the latest machine learning research and incorporate validated techniques into production workflows.

Required Qualifications and Skills

• Minimum of five years’ experience in machine learning engineering with responsibility for production systems.
• Advanced proficiency in Python with comprehensive expertise in PyTorch or TensorFlow frameworks.
• Proven experience training and deploying large-scale ML models, including deep learning, large language models, or traditional ML algorithms.
• Practical knowledge of cloud-based ML platforms such as AWS SageMaker, Google Cloud Vertex AI, Databricks, or equivalent.
• Strong foundation in software engineering principles including testing, code reviews, and system design.
• Track record of delivering ML systems that have measurable impact on business outcomes.

Personal Attributes

• An inquisitive mindset focused on understanding model behaviors and failure modes.
• Meticulous adherence to guidelines with proactive identification and communication of uncertainties.
• Excellent written communication skills, capable of clearly documenting research findings and technical details.
• Ability to work effectively in asynchronous, cross-time-zone teams.

Benefits and Compensation

• Fully remote work arrangement with flexible working hours.
• Competitive base salary ranging approximately between $150,000 and $250,000 USD equivalent, depending on experience and qualifications.
• Performance-based bonuses to reward contribution and impact.
• Annual budget allocated for learning and professional development.
• Health and wellness benefits vary by location.
• Opportunity to work on impactful, large-scale projects deployed in real-world scenarios.

Equal Opportunity

This position is offered on an equal opportunity basis. Applications are encouraged from all qualified candidates without regard to race, color, ethnicity, nationality, gender identity or expression, sexual orientation, age, religion, disability status, marital status, or any other status protected by law. Employment decisions will be solely based on qualifications and merit.