NLP & GenAI Data Scientist – AI Models & MLOps

Calleo Australia; Canberra; On-site; AUD 120,000 - 180,000; Full time

Job summary

Calleo Australia is seeking a skilled NLP/AI specialist to identify and extract skills from diverse data sources and to develop transformer-based and LLM approaches for classification and entity resolution.

The role involves applying GenAI frameworks, evaluating model performance, and collaborating with data engineers to operationalise NLP pipelines within GPU-enabled computing environments.

Qualifications

• Identify, extract, classify and relate skills information from structured and unstructured data sources.
• Develop, adapt and evaluate NLP, transformer-based and Large Language Model (LLM) approaches for skills extraction, text classification, semantic similarity, clustering and entity resolution.
• Apply expertise in contemporary artificial intelligence (AI) and generative AI (GenAI) frameworks to develop, test and optimise bespoke model solutions, including within GPU-enabled computing environments.

Responsibilities

• Collaborate with taxonomy, policy and subject matter experts to incorporate skills definitions, terminology, classification rules and validation requirements into analytical workflows and AI-enabled solutions.
• Collaborate with Data Engineers to operationalise NLP and AI models through repeatable data processing, validation and model-serving pipelines.
• Apply software engineering and machine learning operations (MLOps) practices, including version control, testing, reproducibility, model lifecycle management and technical documentation.

Skills

Skills extraction

NLP

Transformers

LLMs

Text classification

Semantic similarity

Clustering

Entity resolution

GenAI

Model evaluation

MLOps

Data pipelines

Software engineering

GPU computing

Tools

GPU computing

Job description

Calleo Australia is seeking a skilled NLP/AI specialist to identify and extract skills from diverse data sources and to develop transformer-based and LLM approaches for classification and entity resolution.

The role involves applying GenAI frameworks, evaluating model performance, and collaborating with data engineers to operationalise NLP pipelines within GPU-enabled computing environments.