Senior AI / ML Engineer (Long Term B2B Contract- Remote EU)

Besedo Global Services AB; United States; Remote; USD 140,000 - 200,000; Full time

Job summary

Besedo is seeking a senior-level AI/ML professional to lead the productionization, deployment, and continuous optimization of ML systems in mission-critical environments. You will ship models to production, design scalable inference services, and drive reliability, cost and performance trade-offs end-to-end.

Join a small, senior ML team building Implio’s AI, work across the full lifecycle from research to production, and influence architecture and best practices while operating autonomously.

Qualifications

• Master’s/PhD or equivalent in CS/engineering/data science with strong math and ML.
• 6+ years of ML engineering and MLOps experience delivering production systems.
• Proven track record deploying models to production with scalable serving, packaging, and observability.
• Expertise in model performance optimization: latency, throughput, quantization, ONNX/TensorRT.
• Strong Python proficiency.
• Hands-on experience with PyTorch, scikit-learn, ONNX/TensorRT.
• CI/CD for ML (GitLab CI), Docker and reproducible workflows.
• Monitoring and reliability: metrics, logging, alerting, SLOs.
• Nice to have: Kubernetes, AWS, FastAPI, SageMaker, feature stores, model registries.

Responsibilities

• Handle the production lifecycle of ML systems: training, packaging, deployment, monitoring, controlled rollouts.
• Design and improve training/retraining pipelines.
• Build high-performance inference services and deployment patterns.
• Drive inference optimization with measurable latency/cost improvements.
• Collaborate with DevOps/SRE for operational excellence.
• Own model versioning, CI/CD, and release workflows.
• Strengthen data and model monitoring with feedback loops.
• Communicate results to stakeholders and translate into business value.
• Ensure model quality through rigorous evaluation and production-grade validation.

Skills

ML engineering

MLOps

Python

CI/CD for ML

Monitoring & reliability

Model deployment

Inference optimization

Data drift monitoring

Experiment tracking

Communication with stakeholders

Education

Master’s/PhD or equivalent in CS/Engineering/DS

Tools

PyTorch

scikit-learn

ONNX

TensorRT

GitLab CI

Docker

Kubernetes

AWS

FastAPI

SageMaker

Feature stores

Model registries

Job description

Who we are

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.

The role

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.

What we’re looking for

• 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 delivering high-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.

What you’ll own

• 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 workflows ensuring 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.

How you’ll work
* 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 Engineers, DevOps and Developers who are passionate about their work and like to have fun in the process.

We welcome applicants of all backgrounds.

How we work together
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