Neara
Jobs at Neara
Let Your Resume Do The Work
Upload your resume to be matched with jobs you're a great fit for.
Success! We'll use this to further personalize your experience.
Recently posted jobs
Software
Develop machine learning and deep learning models that digitize electricity infrastructure from LiDAR, imagery, GIS, and vector data. Build scalable training, serving, QA, and monitoring pipelines; identify data and distribution drift; improve model deployment speed; and apply MLOps best practices. The role also involves defining ML strategies, solving ambiguous problems, collaborating asynchronously across functions, and mentoring junior engineers.
Software
Lead and grow a high-performing engineering team, owning delivery and development practices. Balance people leadership (~60% time) with hands-on system design and production-quality coding (~40%), focusing on large-scale data ingestion, geospatial processing, simulation engines, and platform vs application trade-offs while partnering closely with Product and customer-facing teams.
Software
Hands-on accounting role supporting Australian and UK entities: manage AP, employee expenses, weekly bank reconciliations, monthly payroll (STP), BAS preparation, month-end tasks, and fixed asset register. Work closely with the Financial Controller in a fast-growth technology environment.
Software
Lead the Design product group owning strategy, roadmap, and delivery for engineering-grade grid modelling and simulation tools. Manage a cross-functional team of product, engineering, and SMEs, set vision and prioritisation, improve delivery processes, and stay hands-on with platform and domain challenges to drive high-quality product outcomes.
Software
As a Senior Software Engineer, you'll design and implement features related to digital twins, data abstractions, and structural analysis, leveraging machine learning and algorithms.
Software
Lead design and operation of Neara's ML platform: roadmap for training pipelines, distributed compute, model serving, experiment management, and monitoring. Build tooling to accelerate research-to-production, optimise performance (including custom CUDA/sparse tensors), and enable scalable, secure deployments across cloud and on‑prem environments while mentoring ML engineers.
