Himalayas · Partner listingSenior AI / ML Engineer (Long Term B2B Contract- Remote EU)
Besedo
⌖ United KingdomSalary not providedRemoteContract · Not specified
Source: Himalayas ↗
Location & working arrangementWorking arrangement is supplied by the provider. Check the original advert for attendance and travel requirements.
Provider location / applicant eligibility: Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Guernsey, Holy See (Vatican City State), Hungary, Iceland, Ireland, Isle of Man, Italy, Jersey, Kosovo, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, San Marino, Serbia, Slovakia, Slovenia, Spain, Svalbard and Jan Mayen, Sweden, Switzerland, Ukraine, United Kingdom, Åland Islands
About the role
Who we are
Besedois 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 thisvideo, and discover more about Besedo on ourwebsite.
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 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.
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 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.
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 togetherAt 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 🎉
Originally posted on Himalayas
Skills mentioned in the listing
PythonDockerKubernetesAWSIncident responseCI/CDData scienceMachine learningDeep learningNatural language processing
Recognised skills are extracted from the supplied description using canonical names and aliases. They are mentions, not verified essential requirements. Check the source advert for the employer’s full requirements and location restrictions.
Why these skills appear
Python · desirable
ponse 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 lifecycleo
Docker · requirement-context
NX, 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,
Kubernetes · desirable
/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
AWS · desirable
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 Han
Incident response · desirable
ing 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 m
CI/CD · mentioned
bility, incident readiness, observability, and alerting. Ownmodel versioning, CI/CD, and release workflowsensuring reproducibility and safe delivery to production. Strengthendata & model monitoring(performance, drift
Data science · mentioned
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 engineer
Machine learning · mentioned
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 applic
Deep learning · mentioned
o 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-us
Natural language processing · mentioned
-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 moder