Overview

Executive Director / Principal Machine Learning Engineer role at TWG Global (TWG Group Holdings, LLC). The organization drives innovation and business transformation across multiple industries by leveraging data and AI as core assets. The role is embedded in the UK Data Science team and reports to the Head of the UK AI and Data Science team.Responsibilities

Translate data science prototypes into production-ready pilot ML services tailored to business use casesBuild lightweight pipelines (feature engineering, model packaging, inference services) that integrate with central platforms and meet immediate delivery needsChampion pragmatic MLOps practices (CI/CD for ML, monitoring, observability) to improve reliability without duplicating central engineering’s enterprise frameworksPartner closely with Data Scientists to operationalize models and collaborate with central engineering to plan handoffs of successful pilots for hardening and scaleApply emerging ML engineering techniques (LLM deployment, RAG, vector databases) to accelerate delivery of applied projectsDevelop reusable components and lessons learned for firm-wide adoptionEnsure ML workflows comply with governance, audit, and regulatory requirementsCollaborate with central Engineering, Data, Product, and Security teams to align with firm-wide platforms and standardsProvide technical mentorship to ML engineers, raising the bar for applied delivery and model deploymentFlex into data science tasks when needed: feature engineering, model experimentation, and analytical insightsRequirements

8+ years of experience designing, building, and deploying ML systems in productionProven track record of leading ML engineering projects from prototype to production deliveryDeep expertise in modern ML frameworks (TensorFlow, PyTorch, JAX, Ray, MLflow, Kubeflow)Proficiency in Python and at least one backend language (e.g., Java, Scala, Go, C++)Strong knowledge of cloud ML infrastructure (AWS SageMaker, GCP Vertex AI, Azure ML) and containerized deployments (Kubernetes, Docker)Hands-on experience with ML pipelines, distributed training, and inference scalingFamiliarity with monitoring stacks (Prometheus, Grafana, ELK, Datadog)Experience in regulated industries (finance, insurance, healthcare) with compliance and governance needsStrong communication and collaboration skills, with the ability to mentor others and influence technical directionWorking knowledge of data science techniques (e.g., supervised/unsupervised ML, model evaluation, causal inference, feature engineering)Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or related field (PhD a plus)Preferred Experience

Experience integrating with Palantir platforms (Foundry, AIP, Ontology) as a user/consumerPractical exposure to LLM and GenAI delivery (fine-tuning, RAG, vector search, inference)Experience optimizing GPU clusters or distributed training workloadsFamiliarity with graph databases (Neo4j, TigerGraph) in applied ML contextsBenefits

Work at the forefront of AI/ML innovation in life insurance, annuities, and financial servicesDrive AI transformation for sophisticated financial entitiesCompetitive compensation, benefits, future equity options, and leadership opportunitiesThis is a hybrid position based in the United Kingdom.We offer a competitive base pay plus a discretionary bonus as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits.TWG is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.Seniority level

DirectorEmployment type

Full-timeJob function

IndustriesNote: This job description has been refined for formatting and clarity. It reflects the responsibilities, qualifications, and benefits of the role without altering original content.

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