Senior Machine Learning Engineer
New
Remote-friendly and flexible working arrangements within Australia.Full-TimeSenior
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Required Skills
- PythonPyTorchTensorflowPrompt EngineeringLLMGenerative AI
Requirements
- Proven experience as a Machine Learning Engineer delivering production-grade ML-powered features.
- Strong programming skills in Python and hands-on experience with frameworks such as TensorFlow or PyTorch.
- Solid understanding of the full ML lifecycle, including data processing, model training, evaluation, deployment, and monitoring.
- Experience building and scaling ML systems in production environments with measurable business impact.
- Strong background in generative AI, including LLMs, diffusion models, prompt engineering, RAG, or fine-tuning.
- Familiarity with GenAI platforms such as OpenAI, Hugging Face, or Anthropic, and embedding-based systems.
- Strong product mindset with focus on user experience, experimentation, and outcome-driven development.
- Ability to work independently while collaborating effectively in cross-functional teams.
- Experience building scalable and maintainable ML systems with clear metrics and performance tracking.
- Strong communication skills and ability to contribute to technical discussions and mentoring.
- Commitment to ethical AI, responsible data usage, and scalable model governance.
Responsibilities
- Build, test, and deploy machine learning-powered features that enhance ad generation and creative product experiences.
- Design and implement scalable ML pipelines in collaboration with platform and infrastructure teams.
- Develop, evaluate, and monitor ML models across the full lifecycle, ensuring performance, reliability, and measurable impact.
- Run experiments and A/B tests to validate hypotheses and continuously improve model effectiveness and user outcomes.
- Collaborate closely with product managers, designers, and engineers to translate user needs into ML-driven solutions.
- Contribute to shared ML infrastructure, standards, and best practices across the broader engineering organization.
- Explore and apply state-of-the-art advancements in generative AI, embedding systems, and large language models at scale.
- Support end-to-end system thinking across the entire user journey, from inspiration to insights and recommendations.
View Full Description & ApplyYou'll be redirected to the employer's site
