In-Demand Linux engineer Jobs in Queensland

Senior Data Scientist
Blackbook.ai —Brisbane QLD
- $104,898.03 - $181,875.84 a year
- Full-time
- Hybrid work
- Computer Science
- Research
- Master's degree
Quick Apply
Project Infrastructure Consultant
Brennan IT —Brisbane QLD
- Contract
- Microsoft Access
- Azure
- Management
13d
Field Service Engineer
Metrea Management LLC —Brisbane QLD
- Contract
- Schematics
- Master's degree
- Education
Quick Apply
Senior Backend Engineer (Big Data)
Binance —Brisbane QLD
- Full-time
- Remote
- Bilingual
- Databases
- SQL
- Work from home
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Senior Solution Architect
Datacom —Brisbane QLD
- $213,000 a year
- Full-time
- Microsoft Access
- Azure
- Microsoft Office
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7d

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Senior Data Scientist

Blackbook.ai -
Brisbane QLD

Quick Apply

Job Details

Full-time
$104,898.03 - $181,875.84 a year

Qualifications

CI/CD
Law
Computer Science
Git
Research
Master's degree
Docker
Bachelor's degree
Machine learning
Natural language processing
Scalability
AI

Full Job Description

Blackbook.ai is seeking a Senior Data Scientist / Machine Learning Consultant to lead the full lifecycle of machine learning projects — from problem framing and data strategy through to model development, deployment, and ongoing performance management.

This role sits at the intersection of applied research and production engineering, requiring both deep technical expertise in NLP and LLMs and the ability to translate business problems into scalable AI solutions.

KEY RESPONSIBILITIES

Model Development & Research

Design, fine-tune, and evaluate LLMs and multimodal models (e.g. Qwen, LLaMA) using frameworks such as PyTorch, PEFT/LoRA, ms-swift, and Megatron-LM
Develop and own RAG pipelines, embedding models, and retrieval systems (dense and sparse), including contrastive learning approaches to improve retrieval accuracy
Lead applied NLP work across tasks including text classification, NER, summarisation, OCR, and code generation
Conduct rigorous experimentation, benchmarking, and ablation studies; document findings clearly for technical and non-technical audiences

Production Deployment & MLOps

Containerise and deploy models using vLLM, Triton Inference Server, TensorRT-LLM, ONNX Runtime, and Docker
Build and maintain FastAPI services wrapping model inference endpoints; integrate models into production applications
Own CI/CD pipelines for ML components; manage experiment tracking and model versioning (e.g. ClearML, MLflow)
Monitor deployed models for drift, latency, and quality; iterate based on real-world feedback

Technical Leadership & Collaboration

Act as a technical authority on LLM and NLP best practices across the data science team
Collaborate closely with software engineers, product managers, and domain experts to scope, deliver, and iterate on AI features
Conduct code reviews, define engineering standards, and contribute to a culture of technical excellence
Mentor and guide junior and mid-level data scientists; support skill development through pairing and knowledge-sharing sessions

Research & Innovation

Stay current with the latest advances in LLMs, multimodal AI, and NLP; evaluate and introduce new techniques with business relevance
Represent the organisation's work through publications, conference papers, or technical blog posts where appropriate
Contribute to the development and maintenance of internal benchmarks, evaluation harnesses, and datasets

QUALIFICATIONS & EXPERIENCE

Required

4+ years of professional experience in machine learning engineering or applied data science, with a strong NLP focus
Proven track record fine-tuning and deploying LLMs and transformer-based models in production environments
Deep proficiency in Python and PyTorch; working knowledge of C++ is an asset
Hands-on experience with at least two of: vLLM, Triton Inference Server, TensorRT-LLM, ONNX Runtime
Experience designing and evaluating RAG pipelines, including embedding model fine-tuning and vector stores (e.g. Milvus, Faiss, Pinecone)
Solid understanding of PEFT methods (LoRA, QLoRA, adapters) and distributed training (Megatron-LM or equivalent)
Proficiency with Docker, Git, Linux, and CI/CD practices in an ML context
Bachelor's and Master's degree in Computer Science, Data Science, Mathematics, or a related technical field

Preferred

Experience with multimodal models (vision-language, speech-language) and related benchmarks
Publications or contributions to peer-reviewed NLP/ML conferences (e.g. ACL, EMNLP, NeurIPS, ICLR)
Experience with code generation or domain-specific language (DSL) modelling tasks
Familiarity with speech synthesis pipelines and text normalisation for TTS
Experience mentoring junior engineers or delivering ML education in an academic or corporate context

Pay: $104,898.03 – $181,875.84 per year

Work Location: Hybrid remote in Brisbane QLD 4000

Quick Apply

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linux engineer jobs in queensland

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