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Role Overview

This opportunity is for an Applied Machine Learning Researcher based in Australia, focused on advancing the next generation of conversational AI by enhancing the intelligence, dependability, and naturalness of voice-enabled systems. The role involves addressing applied machine learning challenges where research is directly translated into production enhancements.

Key Responsibilities

Conduct research and advancements in large language model behavior for real-time voice applications and customer workflows.
Design, implement, and analyze fine-tuning experiments, including datasets, training methodologies, evaluation techniques, and model strategies.
Create and maintain comprehensive evaluation frameworks to measure quality, reliability, natural interaction, workflow compliance, and task completion.
Examine live production conversations to identify model limitations, failure trends, and enhancement opportunities.
Develop and execute data methodologies including curation, labeling strategies, and synthetic data generation.
Compare and optimize different model architectures, prompting methods, training techniques, and datasets.
Identify and explain model regressions and the factors affecting performance changes.
Collaborate with engineering teams to safely deploy research-driven improvements into production environments.
Contribute to establishing model release processes, evaluation benchmarks, and quality standards.

Candidate Requirements

Extensive expertise in machine learning with a focus on modern language model technologies.
Demonstrated experience with fine-tuning, assessing, or adapting large language models.
Advanced proficiency in Python programming and handling complex real-world datasets.
Strong background in designing rigorous experimental setups and interpreting their results to guide improvements.
Proven ability to develop or enhance AI model evaluation systems.
Excellent analytical and debugging capabilities to assess and refine model behavior.
Outstanding communication skills to effectively convey technical results.
A product-driven mindset prioritizing real-world outcomes such as performance, latency, and reliability.
Experience with conversational or voice AI, and customer automation is advantageous.
Familiarity with specialized techniques like SFT, preference tuning, DPO, RFT, GRPO, RLHF, LoRA, or QLoRA is beneficial.
Understanding of model serving, inference optimization tools like vLLM, or synthetic data pipelines is a plus.
A PhD in machine learning, natural language processing, or a related discipline is desirable.
Experience within startup or fast-paced product development environments is valued.

Benefits and Work Environment

Option to work fully remotely for candidates located in Australia.
Chance to work with cutting-edge AI technology that directly impacts production systems.
High level of ownership over projects, seeing research implemented into real-world customer solutions.
Collaboration with skilled engineers, researchers, and product experts.
Opportunities for career growth in a fast-paced AI-centric organisation.
Regular team interactions including in-person events.
A culture fostering curiosity, ambition, collaboration, and continuous learning.

Additional Information

This job is posted on behalf of a partner company that manages all applications and subsequent recruitment steps. The recruitment process uses AI-assisted matching to quickly and objectively identify top candidates, with final hiring decisions made by the employer's internal team. Applicant data will be processed respecting relevant privacy laws and may involve AI tools to assist in evaluations. However, human judgment remains central to hiring decisions.

Applied Machine Learning Researcher