Machine Learning Engineer

Application closing date: Friday, 07 October 2022

• 11:59pm, Canberra time (in Canberra)
  

Estimated start date: Monday, 31 October 2022

Location of work: SA

Length of contract: 12 Months

Contract extensions: 2x 12 months

Security clearance: Applicants must have or have ability to obtain (which ever is relevant) Baseline Security Clearance . No Permanent resident (PR's) can apply for the role, each candidate must be Australia Citizens.

Rates: $125 - $145 per hour (inc. super)

The Machine Learning Engineer within the Cognitive Futures team works on diverse projects that deliver advanced tools and services for internal and external stakeholders. Tools and services developed often leverage Natural Language Processing, Deep Learning, Multi-label Classification and other machine learning techniques.

The Candidate Will Have

Experience applying machine learning techniques within software development

Experience writing high quality Python code

Experience with MLOps or DevOps

Experience working as part of a team

Excellent communication skills

Relevant experience and/or qualifications in data science and software engineering

Deliverables Include

Delivering innovative AI/ML production solutions to solve complex business problems.

Researching, designing, implementing, testing, and monitoring AI/ML solutions.

Building AI/ML models from scratch and helping product managers and stakeholders understand results.

Delivering effective documentation and presentations to technical teams and stakeholders.

Building new and improving existing MLOps pipelines

IP Australia is based in Canberra. It is preferred that the successful candidate work from the office with flexible arrangements, however remote working (offsite) will be considered. If based offsite, the candidate would be expected come to the office initially for on boarding (1-2 days) and up to 4 times per year for team meetings at their own expense.

Essential Criteria

Experience in AI/ML technologies and proven ability to deliver successful Machine Learning models, proof-of-concepts, and AI solutions using techniques and technologies such as Natural Language Processing, Deep Learning, Classification, and Image Recognition.

Experience in MLOps or DevOps.

Experience in full stack development.

Desirable Criteria

Effective communication skills with ability to explain or translate complex models and findings to business stakeholders.

Experience with commercial cloud platforms (AWS, Azure, GCP)

Relevant ICT qualifications and / or Industry certifications, and experience in DevOps and MLOps product lifecycle from inception to production.