Senior Machine Learning Engineer

🔥 3 minutes ago

🇪🇸 Spain – Remote

💵 €70k - €80k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 2%

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Speedcast

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1989

📡 Telecommunications

🤝 B2B

💰 $350M Post-IPO Debt - SpeedCast on 2022-02

Telecommunications • B2B

Speedcast is a leading global provider of satellite communications and managed IT/network services focused on delivering connectivity to remote and mobile operations. The company combines VSAT, MSS, LEO services (including authorized Starlink resale and OneWeb integration), cellular backhaul, cloud-enabled network management (SIGMA), IoT, systems integration and professional services to support customers in maritime, energy, mining, broadcast, telecom, government and other enterprise sectors. Speedcast operates a multi-orbit global network and teleports, offering managed connectivity, network management, edge and cloud solutions tailored for remote, maritime and industrial use cases.

📋 Description

• Own the machine learning lifecycle end-to-end, from problem framing through model development, evaluation, deployment, monitoring, and retraining • Design, build, evaluate, and deploy time-series forecasting, anomaly detection, and classification models • Build and maintain feature and training-data pipelines using streaming and batch sources on the data lakehouse • Own MLOps practices including experiment tracking, model versioning and registry, model CI/CD, automated retraining, and monitoring for drift and degradation • Define and promote standards for model development, evaluation, documentation, and governance • Translate business problems into well-framed ML problems • Communicate model behaviour, limitations, and business impact to stakeholders • Collaborate with data engineers to productionize reliable, observable ML services on AWS • Mentor AI Engineers and data scientists on ML best practices, code quality, and evaluation rigour • Participate in Agile ceremonies, backlog grooming, sprint planning, and prioritisation • Evaluate and support adoption of new ML technologies, tools, and architectural approaches

🎯 Requirements

• Candidates must be based in Spain • Existing right to work in Spain required • No visa sponsorship or relocation support available • 5+ years of experience in machine learning, data science, or ML engineering, including delivering and operating models in production • Strong Python programming skills • Deep familiarity with scikit-learn, XGBoost, PyTorch or TensorFlow, and pandas • Strong SQL skills and experience with large analytical datasets • Hands-on experience with time-series modelling, forecasting and/or anomaly detection at scale • Solid grounding in statistics, experiment design, and model evaluation methodology • Hands-on experience with AWS services, including SageMaker, Lambda, Step Functions, S3, and ECR • Experience deploying ML workloads in the cloud • Experience containerising applications using Docker • Experience with MLOps tooling and practices • Experience using Git and working within Agile/Scrum environments • Excellent communication and stakeholder management skills • Experience with streaming data, Kafka/Confluent, Flink, or near-real-time inference is advantageous • Experience with lakehouse architectures, Apache Iceberg, Parquet, medallion/dbt patterns, or Dremio is advantageous • Experience with TimescaleDB is advantageous • Exposure to LLMs and generative AI systems is advantageous • Telecommunications, satellite, networking, or IoT telemetry experience is advantageous • Infrastructure as Code and CI/CD experience is advantageous • Advanced AWS expertise and relevant AWS or ML certifications are advantageous • Experience mentoring engineers or leading technical workstreams is advantageous

🏖️ Benefits

• Global team and international collaboration • Opportunities to develop skills across departments • Internal promotion system with opportunities for new titles and responsibilities • Diverse projects across industries and global customers • Choice between a traditional desk job or working in the field • Career development opportunities

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