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À propos de ce poste Senior Machine Learning Engineer chez Speedcast

Speedcast · Télétravail · Remote-Madrid
Senior Machine Learning Engineer

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, right alongside us, every single day.

Find great opportunities to make an impact. We have a "one team, one dream" mentality. We work together to make great things happen. Working at Speedcast isn't just a job, it's a career that you can take to new levels.


Top reasons why people love working at Speedcast:


  • Our global presence – you get to work with clients and colleagues all over the world, in every continent
  • Talented teammates – your co-workers are the best and brightest in the industry
  • Industry leadership – be part of the latest advancements shaping the future of communications
  • Ability to develop skills – work across departments to gain new skills and valuable experience
  • Choose your environment – we have an environment to fit your temperament. Choose between a traditional desk job or work in the field.
  • Grow your career – Guide your career in the direction you want. Gain new titles and responsibilities through our internal promotion system.
  • Work on diverse projects – every day is different with our customers from a range of industries around the world

Speedcast is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, veteran status, and other protected characteristics. The US EEO is the Law poster is available by visiting the below link:


https://www.eeoc.gov/employers/upload/poster_screen_reader_optimized.pdf

Speedcast does not accept or retain unsolicited résumés or phone calls and/or respond to them or to any third party representing job seekers.

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, right alongside us, every single day.

Find great opportunities to make an impact. We have a "one team, one dream" mentality. We work together to make great things happen. Working at Speedcast isn't just a job, it's a career that you can take to new levels.

Top reasons why people love working at Speedcast:

  • Our global presence – you get to work with clients and colleagues all over the world, in every continent

  • Talented teammates – your co-workers are the best and brightest in the industry

  • Industry leadership – be part of the latest advancements shaping the future of communications

  • Ability to develop skills – work across departments to gain new skills and valuable experience

  • Choose your environment – we have an environment to fit your temperament. Choose between a traditional desk job or work in the field.

  • Grow your career - Guide your career in the direction you want. Gain new titles and responsibilities through our internal promotion system.

  • Work on diverse projects – every day is different with our customers from a range of industries around the world

Speedcast is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, veteran status, and other protected characteristics. The US EEO is the Law poster is available by visiting the below link:

https://www.eeoc.gov/employers/upload/poster_screen_reader_optimized.pdf

Speedcast does not accept or retain unsolicited résumés or phone calls and/or respond to them or to any third party representing job seekers.

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Comment se compare ce salaire pour ML Engineer

Ce poste paie $83,475/yr — en dessous de la fourchette habituelle pour les postes ML Engineer.

$126,780 la médiane $200,000 $289,531

Fourchette typique $160,000–$242,540/yr, à partir de 1,018 annonces ML Engineer comparables sur JobsRadar (rémunération annualisée en USD). Voir les aperçus de salaire pour ML Engineer →

À propos de Speedcast

Speedcast is a leading communications and IT services provider, delivering critical communications services to the Maritime, Energy, Mining, Media, Telecom, Cruise, NGO, Government, and Enterprise sectors. The company leverages its global network platform to provide fully connected systems that harness technologies and applications to transform what remote operations can achieve. With the world’s most comprehensive network, Speedcast enables faster, seamless pole-to-pole coverage from a global hybrid satellite, fiber, cellular, microwave, MPLS, and IP transport network with direct access to public cloud platforms. The company integrates differentiated technology offerings that provide smarte

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