Seeing Machines has developed the world’s most advanced human data-driven technology which enhances transport safety by dramatically reducing fatal accidents every day. We’re on a mission to achieve zero transport fatalities.

With at least 1 million cars on the road using our state-of-the-art operator monitoring technology developed by the passionate team at Seeing Machines, we provide real-time protection from distraction and drowsiness-related driving events. Seeing Machines works with many of the world’s leading brands (including General Motors, Mercedes Benz, Qantas, Caterpillar, Toll) across the transport sectors automotive, commercial road transport (Fleet), and aviation.

Location: Canberra, ACT

Employment Term: Full Time, Permanent

The MLOps Engineer is responsible for improving how Seeing Machines develops, trains and deploys algorithms to support driver and occupant monitoring. A key focus will be on improving how machine learning scientists, research engineers and software engineers can carry out machine learning processes and improving how resources can be utilized, while keeping in mind the need to support prototyping as well as fast and iterative research.

If it sounds a bit like you – read on for more information below, and Apply!

Key Responsibilities:

• Collaborating with Machine Learning Scientists and Machine Learning Engineers to improve processes and procedures for machine learning training and validation.

• Managing the underlying infrastructure, framework, platform and tools that power ML research.

• Where appropriate, improving automation for machine learning locally, with cloud providers and in hybrid configurations.

• Establishing standards and processes around MLOps, and adopting industry best-practices for MLOps.

• Collaborating with other teams/groups in the company to achieve your goals. Close collaborations with DevOps, Information Systems will be key to the success of this role.

• Documenting approaches used to the appropriate level to support audits by third parties.

• Supporting quick and easy experimentation with new platforms, for example Google TPU boards.

• Reducing the effort and time required for a new team member to get up and running with ML compute resources.

• Comply with all SM policies and procedures, and in particular those relating to work health and safety and equal opportunity.

• Perform other duties as requested, consistent with the level of the position and in line with the principle of multi-skilling.

Knowledge, Skills and Experience:

• An undergraduate degree in Computer Science or similar, or equivalent industry experience.

• Experience writing code in a scripting language like Python or similar in a commercial setting.

• Experience working with large datasets, ideally containing images and videos.

• Experience working in a hybrid environment (on-premise, cloud).

• Experience with container-based technologies (e.g. Docker, Kubernetes) and orchestration techniques (e.g. kubeflow).

• Experience with common machine learning frameworks like TensorFlow and PyTorch.

• Experience with source control systems such as git/Perforce or similar.

• Experience with common cloud providers, such as AWS, Azure, or GCP.

• Ability to work effectively in a team and respond cooperatively to the requirements of other company members.

• Good interpersonal skills with a positive attitude and enthusiasm for continuous improvement.

• Ability and desire to continuously learn new skills.

• Strong written and verbal communication skills with the ability to champion ideas and achieve consensus within a team.

• Self-motivated and proactive with demonstrated ability to set priorities and meet deadlines.

• Ability to operate and plan in a rapidly changing environment.

Desirable

• Experience with automated machine learning workflows.

• Experience with data warehousing solution and their deployment.

• Experience leading initiatives to improve machine learning processes.

• Experience with CI tools such as Jenkins.

• Experience with distributed computing.

Why Seeing Machines

• Being part of something meaningful - We are inventive, innovative and collaborative and are making a real difference to safety on roads, all around the world.

• Work flexibly – we encourage our people to manage their work and personal lives to achieve a balanced outcome.

• Diversely Strong - We are global, Seeing Machines serves a growing market in the UK, Europe, Africa, North America, Latin America, and Asia Pacific.

• We are focused on employee support and understand the importance of our collective wellbeing. You will have access to our Employee Assistance Program any time you require it.

• We reward and recognise achievement. You will have access to our global benefits and reward platform.

For more information, visit: http://www.seeingmachines.com

Seeing Machines acknowledges Traditional Owners of Country throughout Australia and recognises the continuing connection to lands, waters and communities. We pay our respect to Aboriginal and Torres Strait Islander cultures; and to Elders past, present and emerging.