Senior ML/AI Engineering Consultant (expression of interest)

DiUS; Sydney; On-site; AUD 180,000 - 240,000; Full time

Job summary

DiUS is seeking a Senior-Lead ML/AI Consultant to design, train, and deploy production ML and GenAI systems end-to-end for clients in Sydney or Melbourne. This hands-on role goes beyond tool integration, requiring you to justify model design choices and system architectures.

You'll lead client engagements, mentor engineers, and contribute to pre-sales with thought leadership. Hybrid work arrangement with rights to work in Australia.

Qualifications

• Commercial experience designing, building and deploying ML models and systems with hands-on MLOps and production deployment.
• Experience designing, building GenAI, LLM, RAG or agentic systems beyond API integrations.
• Strong Python skills and solid cloud engineering experience.
• Data engineering exposure with big data tooling and platforms like Databricks or Snowflake.
• Consulting skills: stakeholder management, pre-sales experience, and ability to match AI/ML approaches to client problems.
• Passion for staying up-to-date with advancing AI technologies.

Responsibilities

• Lead client engagements end-to-end from requirements to production ML/GenAI deployments.
• Speak to decisions around model design, training, fine-tuning and evaluation.
• Mentor engineers, manage backlogs and drive pre-sales conversations.
• Shaping solutions and scoping to deliver AI/ML projects for clients.

Tools

AWS SageMaker

GCP Vertex AI

Azure ML

Job description

Senior-Lead ML/AI Consultant | Sydney or Melbourne (Hybrid)

We're looking for an experienced ML/AI practitioner who doesn't just use models and AI tools - you build them. Someone who can design, train and ship machine learning and GenAI systems end-to-end, and who enjoys leading clients through hard, ambiguous problems to get there.

This is a hands‑on model/system‑building role, not an AI‑tool‑integration or prompt‑engineering role - you should be able to speak to decisions made in designing, training, fine‑tuning or evaluating a model or agentic system, not just configuring one.

About DiUS

DiUS is an Australian B2B technology services company with an excellent reputation as a trusted consulting partner. We’re a go‑to company for helping organisations of all sizes tackle hard engineering problems, improve delivery practices, modernise applications, and deliver or scale new products to market.

Whether we’re building a product using AI or building an AI experience, we work on problems our clients aren’t able to solve themselves - drawing on our deep range of capabilities across software engineering, experience design, data and analytics, machine learning and AI.

About the role

You’ll lead client engagements end-to-end - from shaping requirements and defining proof-of-concepts through to designing, building, training and deploying production ML and GenAI systems in the cloud. You’ll get hands‑on with everything from classical ML models to agentic and RAG‑based GenAI solutions, while also mentoring engineers, managing a backlog, and showing clients what’s possible.

You’ll also help DiUS keep winning great ML/AI work - supporting pre‑sales conversations, scoping solutions, and sharing thought leadership with clients and the wider practice.

What you’ll bring

• Commercial experience designing, building and deploying machine learning models and systems - proficiency across at least two of NLP, computer vision, recommendation systems or structured data prediction, with hands‑on MLOps and production deployment experience (AWS SageMaker, GCP Vertex AI, Azure ML)

• Commercial experience designing, building and deploying GenAI, LLM, RAG or agentic systems - not just integrating with a hosted API or no‑code agent platform. Comfortable across foundation model providers (Anthropic Claude, OpenAI, Gemini, open‑weight models), agentic frameworks (Bedrock AgentCore, LangChain/LangGraph, CrewAI, AutoGen), MCP, vector databases, and GenAI evaluation/observability tooling

• Strong Python skills and a solid foundation in software development and strong cloud engineering experience

• Data engineering exposure - big data tooling, data modelling, and platforms like Databricks or Snowflake, is a strong plus

• The consulting chops to match: comfort with ambiguity, polished communication style, strong stakeholder management, pre‑sales experience, and the ability to quickly judge which AI/ML approach actually fits a client’s problem

• A genuine passion for staying on top of a fast‑moving AI landscape and separating what’s useful from what’s hype

Why join us

You’ll work alongside a team that takes AI and ML seriously - not as a buzzword, but as a discipline. You’ll have exposure to a variety of different projects featuring different tech, the autonomy to lead client engagements, the platform to shape how DiUS delivers AI/ML work, and a practice that backs continuous learning and thought leadership.

Ready to apply?

You’ll need current working rights in Australia. If this sounds like you, we’d love to hear from you.