wagey.ggwagey.gg
38,923  jobs38,923  jobs
Browse Tech JobsCompaniesFeaturesPricingFAQs
Log InGet Started Free
Jobs(38,923)/Machine Learning Engineer Role(464)/preply (43) - Staff Machine Learning Ops Engineer
Pro members applied to this job 36 hours before you saw itGet Pro ›
preply

preply - Staff Machine Learning Ops Engineer

London+ Equity2d ago
In OfficeStaffEMEACloud ComputingArtificial IntelligenceMachine Learning EngineerPerformance ManagementGCPKubernetesAWSVectorData QualityGovernanceMentoring

Requirements

• 9+ years of engineering experience, with significant depth in large-scale ML, data, infrastructure, or platform systems. • Proven ability to architect and scale production-grade ML platforms that support many teams, workflows, and ML use cases. • Deep understanding of cloud-native architecture and end-to-end ML workflows, including experimentation, feature management, model versioning, training, deployment, monitoring, performance benchmarking, and lifecycle management. • Strong hands-on experience with cloud platforms such as GCP or AWS, Kubernetes, distributed compute, CI/CD, observability, and infrastructure-as-code practices. • Experience building enabling tools and platform capabilities for Applied Scientists, Data Scientists, and engineering teams. • Strong technical judgment and the ability to make pragmatic architecture decisions across reliability, scalability, security, cost, and developer experience. • Excellent communication and influence skills, with experience aligning cross-functional stakeholders and translating platform strategy into execution. • Demonstrated ability to mentor engineers, raise engineering standards, and multiply the impact of teams around you. • Product-impact mindset: you care about building platform capabilities that accelerate experimentation, improve user experiences, and unlock measurable business value. • Familiarity with LLM frameworks and GenAI infrastructure, such as LangChain, LlamaIndex, vector stores, retrieval systems, prompt evaluation, model serving, or LLM observability.

Responsibilities

• Define the technical vision and roadmap for Preply’s ML platform, ensuring it can support growing ML and GenAI adoption across multiple teams, products, and business lines. • Lead the architecture of platform capabilities across the full ML lifecycle: experimentation, feature engineering, artifact management, training, deployment, monitoring, retraining, and governance. • Design cloud-native infrastructure for distributed training and inference, including GPU-based environments, autoscaling, workload isolation, rollout strategies, and cost optimization. • Set the technical direction for CI/CD for ML, embedding testing, validation, security, performance checks, and release confidence into deployment pipelines. • Establish observability standards for ML systems, including model metrics, service health, alerts, drift detection, data quality, lineage, and business-impact monitoring. • Lead the evolution of Preply’s GenAI and LLM platform capabilities, including building LLM Gateway services, vector retrieval infrastructure, prompt experimentation, evaluation frameworks, latency-optimized inference, and reliable model-serving patterns. • Partner with Applied Science and Data leads, Product leaders, and Engineering teams to align platform investments with experimentation velocity, cost efficiency, operational reliability, and user impact. • Design platform abstractions, internal libraries, templates, and self-service tooling that help ML Scientists and engineers move faster without compromising reliability or security. • Act as a technical multiplier across engineering by mentoring senior engineers, influencing architecture, raising standards, and guiding teams through complex platform decisions. • Identify and eliminate bottlenecks in the path from ML research to production, making the platform easier, safer, and more efficient for all ML-powered product development.

Benefits

• Preply’s next stage of growth depends on making AI a scalable company-wide capability, not a collection of isolated models and experiments. This role will define how ML systems are built, deployed, monitored, and improved across the company. • You’ll shape the platform that powers personalized learning, smarter experiences for tutors and learners, marketplace intelligence, content generation, automation, and future GenAI products. The goal is to make it dramatically easier for teams to turn ML ideas into reliable, secure, cost-efficient product experiences at a global scale. • An open, collaborative, dynamic and diverse culture; • A generous monthly allowance for lessons on Preply.com http://preply.com/, Learning & Development budget and time off for your self-development; • A competitive financial package with equity, leave allowance and health insurance; • Access to free mental health support platforms;

Apply in one click

Upload My Resume

Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT

Apply in One Click
Apply in One Click

Similar roles

facultyfaculty - Copy of Lead Machine Learning Engineer3w ago
·London
In OfficeEMEAStaffCloud ComputingArtificial IntelligenceMachine Learning EngineerTeam ManagementCoachingPythonscikit-learnAWSAzureGCPDockerKubernetesFull StackMentoring
Vestiaire CollectiveVestiaire Collective - Senior/Staff Machine Learning Engineer2w ago
·Paris
In OfficeEMEAStaffCloud ComputingArtificial IntelligenceMachine Learning EngineerMLOpsFastAPIRayAWSTritonSnowflakeAzureGCPAirflowMetaflowWeights & BiasesMLflowRedisdbtKubeflowE-commerceExcelVectorONNXDockerKubernetesTerraformPrometheusDatadogvLLM
Vestiaire CollectiveVestiaire Collective - Senior/Staff Machine Learning Engineer2w ago
·Berlin
In OfficeEMEAStaffCloud ComputingArtificial IntelligenceMachine Learning EngineerMLOpsFastAPIRayAWSTritonSnowflakeAzureGCPAirflowMetaflowWeights & BiasesMLflowRedisdbtKubeflowE-commerceExcelVectorONNXDockerKubernetesTerraformPrometheusDatadogvLLM
spotifyspotify - Machine Learning Engineer - Personalization, Horizon1mo ago
·London / New York, NY - Europe *
In OfficeEMEACloud ComputingArtificial IntelligenceMachine Learning EngineerApache SparkGCPAWS
spotifyspotify - Staff Machine Learning Engineer - Content Intelligence1mo ago
·London / Stockholm
RemoteEMEAStaffArtificial IntelligenceOil & GasMachine Learning EngineerData Quality
encordencord - Machine Learning Engineer1w ago
·London·Equity
In OfficeEMEAMidCloud ComputingArtificial IntelligenceMachine Learning EngineerPythonKerasRESTGCPAWSCUDAKubernetesGraphQLFull Stack
Insider OneInsider One - Senior Machine Learning Engineer (Agentic AI)1mo ago
·Remote - Istanbul, Turkiye·Equity
RemoteEMEASeniorCloud ComputingArtificial IntelligenceSoftwareMachine Learning EngineerPythonSQLAWSKubernetes
Mistral AIMistral AI - Applied AI, Forward Deployed Machine Learning Engineer, Critical and Sovereign Institutions, EMEA2mo ago
·Paris
In OfficeEMEACloud ComputingArtificial IntelligenceMachine Learning EngineerReactPythonAWSAzureGCP
algo1algo1 - Machine Learning Engineer4mo ago
·London, England, United Kingdom·Equity
In OfficeEMEAMidCloud ComputingArtificial IntelligenceMachine Learning EngineerJAXPythonAWSGCPAzure

Browse more by category

Show 464 moreMachine Learning EngineerShow 1,394 morePerformance ManagementShow 1,526 moreGCPShow 1,860 moreKubernetesShow 3,747 moreAWSShow 369 moreVectorShow 787 moreData QualityShow 1,808 moreGovernanceShow 1,304 moreMentoring
Privacy·Terms··Contact·FAQ·Wagey on X