Machine Learning Engineer - Satellite Fleet Automation job opportunity at ICEYE.

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Date2025-12-02T06:40:32.188Z bot
ICEYE Machine Learning Engineer - Satellite Fleet Automation
Experience: 4-years
Pattern: Full-time
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degreeHigh School (S.S.C.E)
loacation Helsinki, Finland
loacation Helsinki....Finland

Job Title: Machine Learning Engineer - Satellite Fleet Automation Location: Espoo, Finland (Hybrid) Team: FCC Type: Full-Time, Permanent *Employment is subject to applicable security screening (including SUPO, where required) Who are we? ICEYE is the global leader in synthetic aperture radar (SAR) satellite operations for Earth Observation, persistent monitoring, and natural catastrophe solutions; owning and operating the world's largest SAR constellation. ICEYE is headquartered in Finland and operates from five international locations with more than 600 employees from nearly 60 countries, inspired by the shared vision of improving life on Earth by becoming the global source of truth in Earth Observation. Our satellites acquire images of Earth at any time – even when it’s cloudy or dark – providing commercial and government partners with unmatched persistent monitoring capabilities. Information derived from our SAR images helps customers make data-driven decisions to address time-critical challenges in various sectors, such as maritime, disaster management, insurance, and finance. Our team is a tight-knit group of experts across many disciplines (e.g., engineering, software development, radar technology, etc.). We’re innovative, driven people who strive for excellence in everything we do. Teamwork, curiosity, and having fun are core values at ICEYE, and contribute to Making the Impossible possible!! Why should you work for us? ICEYE is at the cutting edge of new technology and we are continuing to build and operate our commercial constellation of SAR satellites. Working with ICEYE, you will be part of making the impossible possible, whilst shaping the Earth Observation industry. You will work with varied, diverse and engaged colleagues to further the ICEYE mission. At ICEYE we realise that without great people we can not succeed, therefore you will be an integral, valued and appreciated colleague, with the ability to directly shape the vision and direction of the business. We actively support Continuous Professional Development, and will provide access to a range of avenues to allow you to succeed, including courses, training and attendance at conferences. ICEYE is a place where your development, your growth and your success is a priority. Why this role? We are seeking a highly motivated Machine Learning Engineer to join our Fleet Automation team. You will be responsible for developing and deploying AI-based solutions critical for the automated operation of our world-leading SAR satellite constellation. The immediate focus will be on building an advanced anomaly detection system for satellite telemetry to accommodate the needs of our expanding fleet. This role is essential for achieving the ultimate goal of satellite operations automation. You will tackle significant challenges in time-series analysis, feature engineering, MLOps, and working with large volumes of telemetry data . The resulting system must help operators spot problems faster, and make root cause analysis easier. Responsibilities Model Development: Design, develop, and validate robust, scalable Machine Learning models, for telemetry anomaly detection. MLOps & Deployment: Build and maintain MLOps pipelines for model training , monitoring, and deployment of containerized ML components. Data Pipeline: Collaborate with the Data Engineers to improve data quality and  metadata which are essential for model performance and future ML/LLM solutions Research & Innovation: Stay up-to-date with fast-developing ML and LLM techniques and explore their application in new use cases like triaging alerts or analyzing log data. Experience: 4+ years of experience in Machine Learning engineering, focusing on model development, MLOps, and data pipelines. ML Expertise: Deep practical knowledge of various ML techniques, particularly for time-series anomaly detection (e.g., unsupervised, semi-supervised, and supervised methods), as well as LLMs. Language Proficiency: Strong proficiency in Python for ML/AI development. Data & Feature Skills: Proven track record in data ingestion, and preparation . Experience with SQL (PostgreSQL) and time-series (InfluxDB) databases is a plus. Cloud Native: Experience with cloud providers (e.g., AWS), Docker, and Kubernetes for model training and deployment. Architecture & Design: Ability to design scalable ML/AI solutions for a large number of parameters. Problem Solving: Problem-solving skills and ability to identify, research and resolve new problems, including those involving new technologies. Modern Tooling: Keen interest and pragmatic experience in using AI/LLM tools assisting software development. Agility: Ability and willingness to learn new skills in a fast-paced environment, especially in the rapidly evolving GenAI and LLM domain. Communication: Fluency in English and a collaborative mindset, necessary for cooperation with operations and sub-system teams.

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