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Principal Data Scientist (AI Model R&D)

Nearmap Ltd.australia, australia, Australia

5 days ago

Job description

Kindly note that we are currently OOO as a company, and will be back online for application reviews from the week beginning 6th January. Happy holidays!

Nearmap is the Australian-founded, global tech pioneer innovating the location intelligence game. Customers rely on Nearmap for consistent, reliable, high-resolution imagery, insights, and answers to create meaningful change in the world and propel industries forward.

Harnessing its own patented camera systems, imagery capture, AI, geospatial tools, and advanced SaaS platforms, Nearmap stands as the definitive source of truth that shapes the livable world.

The Principal Data Scientist in the Model R&D team is responsible for developing novel visual deep learning models and managing large-scale, cloud-based multi-node training systems. This role involves maintaining and evaluating existing models and systems, developing innovative architectures, designing large-scale training and evaluation methodologies, and producing production-ready deep learning models. These models utilise Nearmap's tens of petabytes of high-quality aerial imagery and millions of highly curated labelled images.

As a core member of the R&D team, the Principal Data Scientist is expected to maintain high engineering standards, demonstrate expertise in designing and maintaining large-scale cloud training systems, and stay current with the latest advancements in AI.

Job Description

In this role, you will :

Lead a complex suite of interacting projects; either technical complexity and interdependency, or business / stakeholder interactions.
Play a key leadership role that has far-reaching impact throughout the whole team – through formal reporting lines or technical and / or project leadership, you will drive the culture and technical vision for the team.
Take a very high level of personal responsibility and accountability for projects, capabilities, etc. within the team.

Key skills & experience we are looking for :

Extensive relevant experience, ideally 10+ years in research or industry, resulting in a powerful combination of intuition, pragmatism, theoretical understanding, and impeccable judgment.

Experience with large-scale model training systems or other high-performance computing.

Programming / Tech Environments : Ability to code in scientific Python and experience working on shared codebases to produce production-quality code.

Machine Learning and AI : Strong grasp of machine learning fundamentals (regularization, hyperparameter optimization, validation methods) and recent AI advancements. Experience with machine learning applied to image data is highly desirable.

Cloud Computing : Experience working on AWS or GCP using distributed virtual machines, Docker containers, etc.

Scale : Experience working with large datasets that don't fit into memory and require multiple nodes for efficient computation.

Scientific Approach : Follow the scientific method of formulating hypotheses and applying statistical tests to validate them.

Pragmatism : While extensive knowledge of ML theory is highly valued, pragmatism wins over elaborate theory when it comes to shipping products that work.

Collaboration : We believe data science is a team sport, and are after candidates who can communicate well, share knowledge, and be open to taking on ideas from anyone in the team. Having worked on shared code-bases in a commercial environment is a big plus, but it's the attitude that matters most.

Attention to detail : Showing attention to detail when it counts is important.

Qualifications

Formal education in a technical, data-related field (Minimum of Bachelor’s degree in computer science, engineering, statistics, physics, or a similarly related field). Formal postgraduate qualifications in data science (Masters / PhD) is a plus.

Additional Information

Some of our benefits

Quarterly wellbeing day off - Four additional days off annually for your 'YOU' Days.

Access to LinkedIn Learning.

Wellbeing and technology allowance.

Hybrid flexibility for this role.

Nearmap subscription (of course!).

Stocked kitchen with access to all the snacks you need.

In-office lunch every Tuesday and Thursday at our Sydney CBD office.

Showers available for anyone cycling to work or lunchtime gym-goers!

Working at Nearmap

We move fast and work smart; often wearing multiple hats. We adapted to remote working with ease and are continually looking at ways to improve. We’re proud of our inclusive, supportive culture, and maintain a safe environment where everyone feels a sense of belonging and can be themselves.

If you can see yourself working at Nearmap and feel you have the right level of experience, we invite you to get in touch.

Thanks, but we got this! Nearmap does not accept unsolicited resumes from recruitment agencies and search firms. Please do not email or send unsolicited resumes to any Nearmap employee, location or address. Nearmap is not responsible for any fees related to unsolicited resumes.

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