Senior ML Engineer — Time-Series & MLOps (Remote, Spain)

SC Comm India-IND; España; Remote; EUR 70,000 - 80,000; Full time

Job summary

Speedcast is a global provider of mission-critical communications solutions. We are building a modern lakehouse platform that ingests streaming telemetry from satellite and SD-WAN networks, enabling analytics across the business.

As a Senior Machine Learning Engineer, you will own the full ML lifecycle on this platform, from framing problems with stakeholders to deployment, monitoring, and retraining in production.

Qualifications

• 5+ years of experience in ML, data science, or ML engineering with production models.
• Strong Python skills and experience with scikit-learn, XGBoost, PyTorch or TensorFlow, pandas.
• Strong SQL skills with large analytical datasets.
• Hands-on experience with time-series forecasting or anomaly detection at scale.
• Experience with AWS services (SageMaker, Lambda, Step Functions, S3, ECR) in production.

Responsibilities

• Design, build, evaluate, and deploy ML models on network telemetry and business data.
• Build and maintain feature and training-data pipelines on the data lakehouse.
• Own MLOps end-to-end: experiment tracking, versioning, CI/CD for models, retraining, monitoring.
• Define and promote standards for model development, evaluation, documentation, governance.
• Translate business problems into well-framed ML problems and communicate impact.
• Collaborate with data engineers to productionize models as reliable services on AWS.
• Mentor AI Engineers on ML best practices, code quality, evaluation rigor.
• Participate in Agile ceremonies, backlog grooming, sprint planning.
• Evaluate adoption of new ML technologies and architectures.

Skills

Python

ML ecosystem

SQL

Time-series

Communication

Tools

Docker

SageMaker

Job description

Speedcast is a global provider of mission-critical communications solutions. We are building a modern lakehouse platform that ingests streaming telemetry from satellite and SD-WAN networks, enabling analytics across the business.

As a Senior Machine Learning Engineer, you will own the full ML lifecycle on this platform, from framing problems with stakeholders to deployment, monitoring, and retraining in production.