7 of 7 Feature Engineering Jobs in East London

SageMaker (moving to Azure ML); containerise code and hook into CI/CD. Monitoring & tuning - track drift, response quality and spend; implement automated retraining triggers. Collaboration - work with Data Engineering, Product and Ops teams to translate business constraints into mathematical formulations. A typical day Morning stand-up: align on performance targets and new constraints. Data dive: explore panel behaviour … clean, tested code. Cloud ML: hands-on with AWS SageMaker plus exposure to Azure ML; Docker, Git, CI/CD, Terraform. SQL mastery for heavy-duty data wrangling and feature engineering. Experimentation chops - offline metrics, online A/B test design, uplift analysis. Production mindset: containerise models, deploy via Airflow/ADF, monitor drift, automate retraining. Soft skills: clear More ❯

modelling, and asset behaviour analytics Conduct advanced experimentation and model development, applying deep learning, LLMs, or probabilistic methods as appropriate Build high-performance, production-grade pipelines for data ingestion, feature engineering, model training, and real-time inference Develop and maintain robust APIs and infrastructure for scalable model deployment, monitoring, and versioning Apply rigorous model evaluation, performance tuning, and …/B testing methodologies Continuously monitor model behaviour post-deployment, addressing drift, feedback loops, and retraining strategies Contribute to and influence architectural decisions regarding ML systems and tooling (e.g., feature stores, orchestration frameworks, vector databases) Lead technical discussions, code reviews, and mentoring sessions for junior and mid-level data scientists Lead R&D initiatives by exploring and prototyping novel … machine learning, including supervised/unsupervised learning, NLP, and/or deep learning Experience with large language models (LLMs), transformers, and modern NLP techniques (e.g., fine-tuning, embeddings, prompt engineering) Proven track record in designing, scaling, and maintaining ML systems in production (cloud-native solutions preferred – e.g., Azure, AWS, GCP) Excellent problem-solving skills and a passion for innovation More ❯

platforms using Dataproc, Dataflow, Pub/Sub, BigQuery, Cloud Spanner, and Bigtable. Define and implement real-time and batch processing pipelines for complex use cases involving streaming analytics, ML feature engineering, and automation. Act as a trusted advisor to senior technical and business stakeholders across industries (e.g., telecom, retail, financial services). Drive data quality, governance, lineage, and … security standards across enterprise data pipelines. Mentor engineering teams and lead best practice adoption across data architecture, orchestration, and DevOps tooling. Participate in technical workshops, executive briefings, and architecture reviews to evangelize GCP data capabilities. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related technical field. 12+ years of experience in data … architecture and data engineering with proven skills and leadership in large-scale cloud data programs. 5+ years of advanced expertise in Google Cloud data services: Dataproc, Dataflow, Pub/Sub, BigQuery, Cloud Spanner, and Bigtable. Hands-on experience with orchestration tools like Apache Airflow or Cloud Composer. Hands-on experience with one or more of the following GCP data More ❯

Principal ML/AI Engineer - Python | Greenfield AI Platform (Contract) We are seeking a Principal/Senior AI/ML Engineer with a strong foundation in software engineering and Python development, to join a globally renowned organisation at the forefront of AI innovation. This is a rare chance to work on greenfield AI/ML projects, delivering transformative solutions … systems using Python and modern frameworks. Lead technical design discussions and influence system-level decisions across greenfield initiatives. Build and scale end-to-end ML pipelines, including data ingestion, feature engineering, model training, and deployment. Champion best practices in software engineering: CI/CD, testing, containerisation, version control, and code quality. Collaborate with cross-functional teams including … data scientists, platform engineers, and product stakeholders to align AI solutions with business goals. Experience Strong commercial experience in Python with a deep understanding of software engineering principles. Demonstrated expertise in building ML systems in production environments (not just notebooks or research). Proven leadership experience in either a senior IC or tech lead/managerial capacity. Familiarity with More ❯

skills – even better if these skills have been applied to threat detection, malware analysis, phishing and/or abuse detection. Experience building production-grade AI pipelines, including data ingestion, feature engineering, validation, model deployment, and monitoring. Experience designing and implementing anomaly detection, classification, clustering, and retrieval across vision and language models, ideally for identifying cyber threats (URLs, domains … fit to problem space, including scenarios where RAG is applicable. Incident response experience, and ability to work with large, noisy, and rapidly evolving threat datasets. Strong background in cloud engineering and containerisation (Docker, Kubernetes) with experience deploying AI services at scale, particularly on AWS via Terraform. The package offered to the Senior/Principal AI Engineer will consist of More ❯

You have experience optimising solution performance with a constrained set of technologies. You have experience or are keen to engage with productionising machine learning technologies combined with large scale feature engineering. More ❯

Job Title: Data Scientist Location: London, UK (Hybrid) Job Type: Permanent Job Description: Experience: Minimum of 8+ years. Skilled Required: LLM, RAG, Finetuning, NLP, Text Summarisation, ML, Feature Engineering Llamaindex, LangChain, LangSmith Vector DB, Vector Search, FAISS Embeddings Experience with OCR, layout models PDF and text file parsing, along with various other file types Experience with REST API More ❯