AI/ML Computational Scientist

Accenture; City of Melbourne; On-site; AUD 180,000 - 260,000; Full time

Job summary

Accenture in Melbourne seeks a Senior AI/ML Computational Scientist to design, build, and operationalize AI/ML solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes.

You will drive the full lifecycle from data assessment and model selection to scalable MLOps pipelines, ensuring quality, value, and reliability of deployed systems at scale.

Qualifications

• Minimum of 7 years of experience as a machine learning engineer or scientist deploying models in production at scale.
• Minimum of 7 years of experience in applying theoretical foundations of computer science including computer system architecture, system engineering, and programming.
• Minimum of 5 years of experience in distributed computing systems and architecture that may include big data, HPC, engineering simulations, grid and cloud computing, distributed networks.
• Minimum of 4 years of experience in building and deploying AI/ML based software to a cloud environment.
• Proficiency in Python and Python-based AI/ML framework and familiarity with libraries such as TensorFlow or PyTorch.
• Experience working with language models like LLM APIs and optimizing their usage for specific applications.
• Experience with Python, C++, Java, R, SQL.
• Strong written & verbal communication skills and ability to explain complex concepts to non-technical stakeholders.
• Strong client-facing skills in a consulting environment.
• Strong cross-functional collaboration abilities.
• Entrepreneurial mindset with curiosity for emergent tech and driving innovation.
• MS or PhD in related field preferred.

Responsibilities

• Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions.
• Develop and implement machine learning algorithms, models, and computational systems; design scalable data pipelines to support model training and production with DevOps & MLOps.
• Customize and apply Deep Learning and Gen AI models for various use cases based on business needs, data availability, system and infrastructure requirements – including edge devices and HPC.
• Engage in research and development of new AI and high-performance compute algorithms, models, and simulations with applications to solve complex business problems at client sites.
• Work with large-scale datasets and preprocessing techniques to ensure high-quality input for training and production.
• Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools.
• Justify the value of model approaches in business problems.
• Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and production integration.

Skills

ML Engineer

Distributed computing

Python proficiency

LLM APIs

Cross-functional

Consulting

Entrepreneurial mindset

Education

Bachelor's Degree or equivalent

MS or PhD preferred

Job description

YOU ARE

As a senior AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. Your role spans the full solution lifecycle — assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and MLOps/LLMOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.

THE WORK

• Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions

• Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps & MLOps

• Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC

• Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites

• Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production

• Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools

• Justify the value of model approaches in business problems

• Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production

EDUCATION

• Bachelor's Degree or equivalent

BASIC (REQUIRED) QUALIFICATION

• Minimum of 7 years of experience as a machine learning engineer or scientist, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing.

• Minimum of 7 years of experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming

• Minimum of 5 years of experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks

• Minimum of 4 years of experience in building and deploying AI/ML based software to a cloud environment.

PREFERRED QUALIFICATION

• Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch)..

• Experience working with language models like LLM's APIs and optimizing their usage for specific applications.

• Experience with the following programming languages: Python, C++, Java, R, SQL

• Strong written & verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders

• Strong client-facing skillsets in a consulting environment

• Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams

• Entrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation

• MS or PhD in related field preferred (computer science, engineering, etc.)