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Posted 7 months ago

Senior Machine Learning Engineer (Freelance - Remote EU)

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AI Summary

Leads the productionization, deployment, and optimization of ML systems for content moderation at scale, combining deep ML expertise with MLOps and production engineering to deliver reliable, high-performance AI services.

About this role

Who are we?

Besedo is a tech company delivering Trust & Safety solutions to online marketplaces worldwide. Every year, we review and moderate over 500 million pieces of user-generated content and block more than 40 million fraud attempts – helping online platforms stay safe and trusted for millions of users. Besedo has headquarters in Stockholm (Sweden) and employs over 350 employees in 5 offices in different countries. Implio is our all-in-one SaaS moderation platform that combines state-of-the-art AI (deep learning, NLP, computer vision) with a powerful user interface for human moderation and powerful analytics. The result is an easy-to-use content moderation solution that enables companies to reduce risks, protect their users and build safer online environments.

Learn more about Implio in this video, and discover more about Besedo on our website.

Job description

We are looking for a senior-level AI/ML professional to lead the productionization, deployment, and continuous optimization of ML systems in mission-critical environments. This role requires strong technical leadership, deep hands-on experience shipping models to production, and the ability to drive reliability, scalability, and cost/performance trade-offs end-to-end. The ideal candidate combines strong ML depth with MLOps and production engineering excellence, and can operate autonomously while influencing architecture and best practices across teams.

You’ll join a small, senior ML team building the AI behind Implio, which moderates user-generated content for online platforms at scale. You’ll work across the full lifecycle, from model research to production, and help shape how we build and ship ML.

Key Qualifications

  • Master’s, PhD, or equivalent experiencein Computer Science, Engineering, Data Science (or related), with strong foundations in mathematics, statistics, and ML.

  • 6+ years(or equivalent) experience across ML engineering and MLOps/production ML, with a proven track record deliveringhigh-impact systems in production.

  • Demonstrated expertise deploying models to production: scalable serving patterns, model packaging, inference optimization, observability, and safe rollout strategies.

  • Strong experience withmodel performance and efficiency optimization: latency/throughput tuning, batching, quantization, ONNX/TensorRT, GPU/CPU optimization, memory and cost tuning.

  • Strong proficiency inPython.

  • Hands-on experience with ML frameworks such asPyTorch, scikit-learn, and optimization/runtime stacks likeONNX, TensorRT.

  • Strong grasp ofCI/CD for ML(e.g., GitLab CI), containerization (Docker), and reproducible workflows.

  • Experience withmonitoring and reliability: metrics/logging/tracing, model/data drift, alerting, SLOs, incident response practices.

  • Plus (nice to have):Kubernetes, AWS, FastAPI (and/or similar Python serving frameworks), SageMaker, service meshes, feature stores, model registries.

Key Responsibilities

  • Handle the production lifecycleof ML systems: training, packaging, deployment, monitoring and controlled rollouts.

  • Design, build, and continuously improvetraining and retraining pipelines(data ingestion, labeling/QA loops, feature generation, experiment tracking, reproducibility).

  • Build and improvehigh-performance inference servicesand deployment patterns.

  • Driveinference optimization(ONNX/TensorRT, quantization, batching, GPU/CPU tuning) with measurable latency/cost improvements.

  • Partner with DevOps/SRE to ensureoperational excellence: scaling, reliability, incident readiness, observability, and alerting.

  • Ownmodel versioning, CI/CD, and release workflowsensuring reproducibility and safe delivery to production.

  • Strengthendata & model monitoring(performance, drift, quality) and implement feedback loops for continuous improvement.

  • Communicate results and trade-offs to stakeholders, turning technical outcomes into business value.

  • Ensure model quality through rigorous evaluation and production-grade validation aligned with evolving data and business needs.

About this position
This role is 100% remote, so you can work from anywhere in the EU and set up your days in a way that works best for you. You will work with a team of talented Machine Learning Engineer DevOps and Developer who are passionate about their work and like to have fun in the process. We welcome applicants of all backgrounds.

What it’s like working with us?
At Besedo, we all come from different cultures and backgrounds, but we share a common set of values:

  • We like to get things done ✔️

  • We support each other to reach our goals and grow as professionals🤝

  • We love to learn, share and have fun together 🎉

Skills

AWSBatchingCI/CDDockerFastAPIGitLab CIGPU OptimizationInference OptimizationKubernetesMLOpsModel DeploymentModel MonitoringONNXPythonPyTorchQuantizationSagemakerSciKit-LearnTensorRT

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