Overview
Join to apply for the Machine Learning Engineer role at Sitemate
This range is provided by Sitemate. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
A$115,000.00/yr - A$200,000.00/yr
Responsibilities
* We’re looking for a Machine Learning Engineer to help us build AI products our customers will love. In this role, you’ll primarily be involved in architecting, building, training and deploying models that power our AI products. You’ll collaborate closely with product and design teams to experiment, ship fast, and bring new AI capabilities into production. This role is ideal for an engineer who enjoys end-to-end ownership, problem solving, and shaping how people interact with emerging AI technology.
* Own full AI generation pipelines: data prep/labeling, model selection and fine-tuning, guarded generation.
* Design and ship agentic flows using core product agents and use-case orchestration.
* Build and maintain data pipelines to ensure clean, reliable, and scalable training datasets.
* Collaborate with product managers, designers, and engineers to integrate AI into user-facing features.
* Evaluate and integrate third-party AI services and APIs to accelerate development.
* Deploy, monitor, and continuously improve model performance, accuracy and costs.
* Document workflows, share insights, and contribute to best practices in applied machine learning.
* Participate in code reviews and technical discussions, sharing knowledge and shaping engineering standards.
What you will be doing on a day-to-day basis
* Initial projects will focus on intelligent document processing and conversational AI interfaces.
* Design and ship agentic flows and data pipelines for AI-powered features.
* Collaborate with cross-functional teams to integrate AI into product features.
* Evaluate new features, algorithms, architectures, or approaches and monitor model performance.
* Maintain transparent documentation and contribute to engineering best practices.
Biggest challenges
* Navigating emerging AI technologies and evolving APIs/frameworks.
* Defining technical foundations and standards for AI products in a growing company.
* Balancing experimentation with reliability and production readiness.
* Data augmentation with limited labeled data; managing cost and latency at scale.
Who This Role Is For
* Enjoys working with emerging technologies (specifically AI) and thrives in areas where the playbook is still being written.
* Cares deeply about creating best-in-class user experiences, not just backend logic.
* Enjoys fast-paced work, getting stuff done, and running experiments with high impact.
* Can work independently with minimal ML infrastructure in place and educate the broader engineering team.
Who This Role is Not For
* If you want to focus only on backend or only on frontend work, without touching the full stack.
* Uncomfortable with ambiguity, rapid iteration, or shaping new product directions from the ground up.
* Researchers focused purely on novel algorithm development without production considerations.
What We Offer
* Flexible hybrid work arrangements.
* First ML hire with significant influence on technical direction.
* Direct mentorship from engineering leadership.
* Budget for continuous learning and access to the latest AI tools and platforms.
* Opportunity to shape AI strategy.
* Equity options and a standard vesting schedule.
Skills & Tools (Must Have)
* 2+ years shipping production ML/AI features.
* Strong Python for ML and working knowledge of TypeScript.
* Experience with LLMs (fine-tuning, prompt engineering, evaluation).
* Understanding of ML fundamentals (training/validation/test splits, overfitting, metrics like precision/recall).
* Hands-on experience with structured data extraction from unstructured sources.
* AWS cloud experience.
Nice To Have
* Built agentic systems and/or MCP servers.
* Experience with model quantization and optimization techniques.
* MLOps: experiment tracking, model/version management, A/B or shadow testing, rollback strategies.
* Experience building real-time voice features and vector databases/RAG.
* Knowledge of prompt chaining and few-shot learning techniques.
* Data privacy & security for AI workloads (PII handling, auditability, least-privilege IAM).
Essential Tools
* AWS Cloud.
* AI/ML Platforms: OpenAI API, AWS Bedrock.
* Languages: Python and TypeScript/Node.js.
* Version Control: Git, LFS.
* Modern CI/CD: Github actions, AWS CDK.
* Monitoring/observability: ML monitoring tools.
Notes
* We do not use recruitment partners or services; please avoid unnecessary outreach.
* Compensation range: A$115K - A$200K
Employment details
* Seniority level: Entry level
* Employment type: Full-time
* Job function: Engineering and Information Technology
* Industries: Technology, Information and Internet
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