Machine Learning Engineer

Job Description \n TiakiTech is an Auckland-based healthtech startup developing advanced AI technologies for healthcare.

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\n This is an exciting opportunity for a recent PhD graduate to bring their research expertise into an early-stage technology company and work on real-world AI challenges with direct clinical relevance. You will join a small, ambitious R&D team where your work can meaningfully influence both the technical direction and future products of the company.

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\n The Role\n

\n About TiakiTech\n

\n TiakiTech is an Auckland-based healthtech startup developing advanced AI technologies for healthcare.

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\n This is an exciting opportunity for a recent PhD graduate to bring their research expertise into an early-stage technology company and work on real-world AI challenges with direct clinical relevance. You will join a small, ambitious R&D team where your work can meaningfully influence both the technical direction and future products of the company.

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\n The Role\n

\n You will work across applied AI research, algorithm development and technical validation, helping translate advanced methods into practical healthcare technologies.

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\n The role will involve:

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\n Developing and improving ML algorithms and research prototypes

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\n Working with biomedical, physiological and other complex datasets

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\n Designing experiments and evaluating model performance, robustness and reliability

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\n Supporting GPU, HPC and cloud-based research workflows

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\n Collaborating closely with engineers, researchers and clinical partners

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\n Supporting hospital-based research and collaboration activities where required

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\n What We're Looking For\n

\n Essential\n

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\n PhD completed, or thesis submitted for examination by December 2026, in a relevant field (Bioengineering, Biomedical Engineering, Electrical Engineering, Computer Science, AI, Signal Processing or related disciplines)

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\n Strong foundation in ML, statistics and algorithm development

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\n Strong Python programming and modern ML framework experience (PyTorch, TensorFlow, scikit-learn)

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\n Experience with GPU training and/or HPC environments

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\n Strong understanding of model evaluation, validation and experimental design

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\n Experience handling complex or large-scale datasets

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\n Comfortable with scientific software development workflows (Linux, Git, Jupyter, environment management)

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\n Able to work on-site (a must) in Auckland and travel to collaborating hospital sites when required

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\n Desirable\n

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\n Experience with biomedical signals or complex time-series data (ECG, EEG, PPG, wearable sensing)

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\n Experience with cloud-based ML infrastructure and scalable compute (AWS, EC2 GPU, S3, Docker or equivalent platforms)

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\n Familiarity with emerging AI technologies (LLMs, AI agents, foundation models)

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\n Exposure to healthcare, clinical research or regulated technology environments

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\n Employment\n

\n This is an initial 6-month full-time fixed-term R&D position associated with a defined R&D programme.

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\n There may be an opportunity for subsequent permanent employment, subject to ongoing business and R&D requirements, funding and mutual agreement.

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\n Location: Auckland, New Zealand

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\n Work arrangement: On-site

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