Staff Machine Learning Engineer - Platform

About Neara and the Role

At Neara, we empower power grid operators globally to prepare for extreme weather events by creating physics-informed digital twins powered by advanced machine learning. Our technology spans electricity networks across four continents, helping asset owners identify risks and implement resilient solutions across vast infrastructure networks.

Our team combines deep expertise in AI and machine learning to accelerate data classification and complex scenario modeling. We foster an innovative environment where each team member drives the mission forward, scaling our impact worldwide.

The Staff Machine Learning Platform Engineer will be responsible for leading the design and operation of robust infrastructure that enables fast, reliable, and scalable deployment of our complex machine learning solutions. These solutions address novel challenges such as multi-modal spatial models using geospatial and point cloud data in a pioneering research space with unique performance and deployment constraints.

Key Responsibilities

• Lead the end-to-end ML platform strategy by shaping a multi-year roadmap encompassing training pipeline development, serving infrastructure, experiment tracking, and monitoring frameworks.
• Build foundational tooling to streamline ML production workflows, enhancing speed from ideation to deployment by standardizing and removing barriers.
• Solve challenging distributed systems issues, ensuring efficient model training across diverse datasets under security and residency guidelines, optimizing performance on varied GPU hardware including sparse tensor operations.
• Architect scalable serving solutions that can handle variable production loads, permitting experimentation across different regions, clients, and verticals.
• Identify and remove bottlenecks slowing the ML team, establish clear interfaces among training, evaluation, and serving components, and drive ambitious research into routine production delivery.

Qualifications and Experience

• Extensive practical experience in developing and managing scalable ML training pipelines, distributed computing platforms, model serving, and monitoring systems.
• Expertise in writing and optimizing custom CUDA kernels for deep learning, especially for non-traditional data formats, with the ability to troubleshoot sparse architecture performance issues.
• Proven background in production model monitoring, building data quality frameworks, and preparing training data warehouses for ML workflows.
• Demonstrated leadership in setting ML platform standards and influencing complex infrastructure choices across diverse teams without direct reporting lines.
• Advanced proficiency in Python and PyTorch or equivalent frameworks, coupled with solid system design skills and an R&D mindset for prioritization.
• Experience with cloud platforms such as AWS, GCP, or Azure, container technologies including Kubernetes and Docker, and operating within on-premises or neocloud settings.
• Track record of mentoring and uplifting ML engineering teams through active leadership, documentation, and establishing internal best practices.

Benefits and Culture

• Competitive compensation package including salary and equity (ESOP).
• Flexible working environment with a fully equipped office space located in Redfern, including a well-stocked snack selection.
• Engaging regular office events and a supportive, diverse culture where innovation and impact are valued.

Additional Information

Neara is committed to diversity, inclusion, and providing equal employment opportunities. Applicants from all backgrounds are encouraged to apply. Note: third-party agencies or service providers need not apply.