Senior Machine Learning Engineer - Image Design Generation [Remote]

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Machine Learning Engineer - Image Design Generation based in Australia.

This role offers the opportunity to build advanced generative AI systems that transform how millions of people create and interact with digital designs.
You will work at the intersection of machine learning research, engineering, and product development to bring innovative image generation capabilities into production.
The position focuses on designing, deploying, and optimizing models that deliver high-quality, scalable, and reliable creative experiences.
You will collaborate with talented ML engineers, backend engineers, product teams, and researchers to turn emerging AI techniques into real-world solutions.
This is a highly autonomous role where you will own projects end-to-end, from experimentation and prototyping to measurable impact in production.
You will contribute to the future of AI-powered creativity while working in a fast-paced, collaborative, and innovation-driven environment.

Accountabilities:

As a Senior Machine Learning Engineer specializing in Image Design Generation, you will develop and scale machine learning systems that power advanced image creation experiences. You will contribute across the full ML lifecycle, from research exploration and model development to production deployment and optimization.

• Design, develop, and deploy machine learning models and systems for image generation and editing capabilities.
• Collaborate with ML engineers, backend engineers, frontend teams, and product partners to deliver user-facing AI features.
• Research and evaluate the latest advancements in deep learning and generative AI, transforming promising techniques into production-ready solutions.
• Contribute to the development and optimization of generation methods tailored to different user needs and experiences.
• Investigate and resolve challenges related to model quality, latency, scalability, and reliability within production environments.
• Build and maintain ML infrastructure, pipelines, and deployment systems required to operate generation models at scale.
• Improve model performance by balancing generation quality, speed, reliability, and practical product requirements.
• Take ownership of technical projects from initial concepts and experiments through implementation and measurable business impact.
• Communicate complex technical concepts clearly with both technical and non-technical stakeholders.
• Share knowledge, contribute to engineering best practices, and support continuous improvement across the team.

Requirements:

The ideal candidate is an experienced machine learning engineer with a strong background in building and deploying production ML systems. You should be comfortable working across model development, infrastructure, and product integration while demonstrating autonomy and strong problem-solving skills.

• Proven experience building and shipping machine learning models in production environments.
• Strong understanding of deep learning concepts, generative AI techniques, and modern ML research practices.
• Hands-on experience with image generation, computer vision, diffusion models, or related AI technologies is highly preferred.
• Experience moving models beyond experimentation into scalable, reliable production systems.
• Strong programming skills and experience working with machine learning frameworks and engineering tools.
• Ability to design and maintain ML pipelines and infrastructure for large-scale model serving.
• Understanding of production trade-offs between model quality, performance, latency, and reliability.
• Ability to independently drive projects from ideas and prototypes through deployment with minimal supervision.
• Strong analytical thinking and ability to solve complex technical challenges.
• Excellent communication skills with the ability to explain technical concepts clearly.
• Experience collaborating within cross-functional engineering and product teams.
• Comfortable working in fast-paced, iterative environments where priorities evolve quickly.
• Curiosity, ownership mindset, and enthusiasm for experimenting with emerging AI technologies.

Benefits:

• Flexible remote-friendly work environment within Australia.
• Opportunity to work on cutting-edge generative AI technologies used by millions of users.
• Equity package allowing employees to share in the company’s success.
• Inclusive parental leave policies supporting different family structures.
• Annual wellbeing and lifestyle allowance to support personal development, social connection, and workspace needs.
• Flexible leave options designed to support wellbeing, recharge time, and personal commitments.
• Collaborative environment with opportunities to learn from experienced engineers, researchers, and product specialists.
• Professional growth opportunities through exposure to large-scale AI systems and innovative technologies.
• Virtual interview process and flexible work arrangements.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.