Senior Machine Learning Engineer

🕒 September 14

🇦🇺 Australia – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 18%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Fleet Space Technologies

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2015

🚀 Aerospace

🔧 Hardware

📡 Telecommunications

💰 $100M Series D - Fleet Space Technologies on 2024-12

Aerospace • Hardware • Telecommunications

Fleet Space Technologies is an Australian space communications company that designs, builds and operates small satellites and supporting ground infrastructure to deliver low-cost, global connectivity for IoT and remote sensors. Fleet develops nanosatellite hardware and terminals and provides a managed satellite network and services to connect remote assets where terrestrial networks are unavailable, targeting industrial and enterprise IoT applications.

📋 Description

• Develop, mature and deploy machine learning models and systems supporting satellite-enabled mineral exploration • Partner with the Senior ML Engineer and Data Science team to transition research models from notebooks and prototypes into production-grade products • Build and maintain robust, efficient ML and data pipelines and supporting infrastructure • Configure GPU environments for scalable machine learning systems • Own model quality across retraining cycles through leakage-safe evaluation and calibrated uncertainty • Maintain reproducible model lineage from configuration through prediction • Own the ML experiment platform, including MLflow tracking, model registry, run identity and provenance conventions • Manage environments and dependencies for training jobs • Partner with the Platform team, reusing shared infrastructure modules and contributing new patterns • Write clean, testable Python using SOLID principles, unit tests and automated end-to-end tests • Monitor developments in ML and MLOps and incorporate useful practices

🎯 Requirements

• Deep expertise in machine learning across modeling, engineering and architecture, with proven experience as a software engineer focused on ML • Proficiency with Python, Pandas, NumPy, scikit-learn, TensorFlow, PyTorch, MLflow, AWS, Databricks, Terraform, GitLab, Zarr and Icechunk • Experience across the full ML lifecycle, from data preprocessing and feature engineering through training, evaluation and deployment • Experience taking research artifacts to production-grade, scalable solutions • Data engineering knowledge including deterministic, idempotent pipelines, schema and contract discipline, and failure and retry semantics • Software delivery knowledge including continuous release, automated gates, observability and application architecture • Solid grounding in MLOps, including model development, deployment and data versioning • Strong Python and software engineering fundamentals across data structures, algorithms and design patterns • Hands-on AWS and Databricks experience, infrastructure as code with Terraform, and well-architected design principles • Experience with code and data version control such as GitLab, MLflow and Icechunk • Experience in startup environments building ML products and environments from early stages • High-ownership and high-agency mindset • Geospatial data experience is a plus • Exposure to big-array data, remote sensing workflows, big data technologies, open-source ML projects, and AI-assisted development workflows is advantageous

🏖️ Benefits

• Extremely flexible work culture with onsite, hybrid and remote working options • Equity (ESOP) grants • 20 days of annual leave • 10 extra Wellness days per year • Learning budgets • Confidential Psychologist appointments via the Employee Assistance Program • Opportunities to participate in the STEM program

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