Senior Machine Learning Engineer

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

Senior Machine Learning Engineer

Location: Remote- Spain: Candidates must be based in Spain and have the existing right to work in Spain. We are unable to offer visa sponsorship or relocation support for this role.

Salary: EUR 70,000-80,000 per annum (depending on experience)

Overview of Position

Speedcast delivers highly customizable, mission-critical communication solutions for remote sites worldwide. Our Data Engineering team operates a modern lakehouse platform - streaming telemetry from satellite and SD-WAN networks through Kafka into Iceberg, TimescaleDB, and a cloud query layer - that powers analytics across the business.

As a Senior Machine Learning Engineer, you will own the machine learning lifecycle on this platform end-to-end: from framing problems with stakeholders, through model development and evaluation, to deployment, monitoring, and retraining in production. Typical problem spaces include network usage and capacity forecasting, anomaly detection on high-volume time-series telemetry, and predictive insights for service quality and cost.

This is a senior role on a small, agile team. You will set the technical bar for how models are built, evaluated, and operated at Speedcast, and you will mentor AI Engineers on machine learning fundamentals and production discipline. The successful candidate works independently, proactively drives improvements, and communicates clearly with both technical and non-technical audiences.

What you will do

• Design, build, evaluate, and deploy machine learning models - including time-series forecasting, anomaly detection, and classification - on network telemetry and business data.
• Build and maintain feature and training-data pipelines on top of the data lakehouse (streaming and batch sources).
• Own MLOps practices end-to-end: experiment tracking, model versioning and registry, CI/CD for models, automated retraining, and monitoring for drift and degradation.
• Define and promote standards for model development, evaluation, documentation, and governance across the team.
• Translate business problems into well-framed ML problems, and communicate model behaviour, limitations, and business impact to stakeholders.
• Collaborate closely with data engineers to productionize models as reliable, observable 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 activities.
• Evaluate and support the adoption of new ML technologies, tools, and architectural approaches.

What we need from you

• 5+ years of experience in machine learning, data science, or ML engineering, including delivering and operating models in production.
• Strong programming skills in Python and deep familiarity with the ML ecosystem (e.g., scikit-learn, XGBoost, PyTorch or TensorFlow, pandas).
• Strong SQL skills and experience working 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 (e.g., SageMaker, Lambda, Step Functions, S3, ECR) and deploying ML workloads in the cloud.
• Experience containerising applications using Docker.
• Experience with MLOps tooling and practices (experiment tracking, model registries, monitoring).
• Experience using Git for source control and working within Agile/Scrum environments.
• Excellent communication and stakeholder management skills, including explaining model behaviour to non-technical audiences.

Even better if you have

• Experience applying ML to streaming data (Kafka/Confluent, Flink) or near-real-time inference.
• Experience with lakehouse architectures (Apache Iceberg, Parquet, medallion/dbt patterns) and query engines such as Dremio.
• Experience with time-series databases such as TimescaleDB.
• Exposure to LLMs and generative AI systems, including evaluation of generative outputs.
• Experience in telecommunications, satellite, networking, or IoT telemetry domains.
• Experience with Infrastructure as Code (e.g., CloudFormation, Terraform) and CI/CD pipelines.
• Advanced AWS expertise, including relevant AWS or ML certifications.
• Experience mentoring engineers or leading technical workstreams.

Working at Speedcast

At Speedcast, we want people that like adventure. Who are motivated by work that takes uncommon ingenuity and thinking outside the box. Who relish the idea of working in an industry undergoing massive transformation. If you want to be part of a global team responsible for connecting the world, then you're in the right place.

We're always pushing forward, never standing still. When people rely on you and your team to stay connected, it brings everyone closer together. We're united by the adrenaline of high-stakes projects and our love of getting the job done right. You will experiment, learn and grow here,