16 of 16 Remote Feature Engineering Jobs in London

ll Bring We are seeking a seasoned professional who is excited by the unique challenges of AI data. Qualifications What are we looking for? Must-Have Skills Extensive Data Engineering Experience: Proven track record (3+ years) in designing, building, and maintaining large-scale data pipelines and data warehousing solutions. Cloud Platform Mastery: Expert-level proficiency with at least one … data technologies like Apache Spark, Kafka, and data orchestration tools such as Apache Airflow or Prefect. ML Data Acumen: Solid understanding of data requirements for machine learning models, including feature engineering, data validation, and dataset versioning. Vector Database Experience: Practical experience working with vector databases (e.g., Pinecone, Milvus, Chroma) for embedding storage and retrieval. Generative AI Familiarity: Understanding … TensorFlow for data preparation in an ML context. Experience with real-time data streaming architectures. Familiarity with containerization (Docker, Kubernetes). Master's or Ph.D. in Computer Science, Data Engineering, or a related quantitative field. Additional Information Starcom has fantastic benefits on offer to all of our employees. In addition to the classics, Pension, Life Assurance, Private Medical and More ❯

their career by working on real AI projects, learning from experts, and gaining hands-on experience with modern AI tools, models, and data pipelines. Whether you studied Computer Science, Engineering, Maths, Data Science, or a related field, if you have a passion for AI and a hunger to learn — we want to hear from you. What You’ll Be … models using tools like Python, TensorFlow, PyTorch, or Scikit-learn. Explore & Prepare Data : Help clean, transform, and analyse large datasets for AI applications. Experiment & Research : Test new algorithms, perform feature engineering, and help improve model accuracy and efficiency. Deploy & Monitor Models : Learn how to deploy models into production environments and monitor their performance over time. Collaborate Across Teams … expecting a seasoned expert — we’re looking for potential , passion , and a strong foundation . Essential: A recent graduate (or soon-to-be) in Computer Science, AI, Data Science, Engineering, Mathematics, Physics, or a similar discipline A strong interest in AI/ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data More ❯

Key Responsibilities Develop, train, and optimize machine learning models for production use. Collaborate with data scientists to turn research prototypes into production-grade solutions. Build robust data pipelines and feature engineering workflows. Deploy ML solutions into cloud environments (AWS, GCP, or Azure). Implement monitoring, testing, and model performance evaluation frameworks. Work with engineering teams to ensure … and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, MLflow). Proficiency in working with cloud services (AWS, GCP, or Azure). Strong understanding of CI/… NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid working model) Day Rate: Competitive, depending on experience More ❯

Key Responsibilities Develop, train, and optimize machine learning models for production use. Collaborate with data scientists to turn research prototypes into production-grade solutions. Build robust data pipelines and feature engineering workflows. Deploy ML solutions into cloud environments (AWS, GCP, or Azure). Implement monitoring, testing, and model performance evaluation frameworks. Work with engineering teams to ensure … and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, MLflow). Proficiency in working with cloud services (AWS, GCP, or Azure). Strong understanding of CI/… NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid working model) Day Rate: Competitive, depending on experience More ❯

Key Responsibilities Develop, train, and optimize machine learning models for production use. Collaborate with data scientists to turn research prototypes into production-grade solutions. Build robust data pipelines and feature engineering workflows. Deploy ML solutions into cloud environments (AWS, GCP, or Azure). Implement monitoring, testing, and model performance evaluation frameworks. Work with engineering teams to ensure … and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, MLflow). Proficiency in working with cloud services (AWS, GCP, or Azure). Strong understanding of CI/… NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid working model) Day Rate: Competitive, depending on experience More ❯

Key Responsibilities Develop, train, and optimize machine learning models for production use. Collaborate with data scientists to turn research prototypes into production-grade solutions. Build robust data pipelines and feature engineering workflows. Deploy ML solutions into cloud environments (AWS, GCP, or Azure). Implement monitoring, testing, and model performance evaluation frameworks. Work with engineering teams to ensure … and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, MLflow). Proficiency in working with cloud services (AWS, GCP, or Azure). Strong understanding of CI/… NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid working model) Day Rate: Competitive, depending on experience More ❯

Machine Learning Engineer Are you excited by the idea of building intelligent systems that learn from data? Are you looking to start a career at the intersection of software engineering and data science? We are looking for a motivated and curious Graduate Machine Learning Engineer to join our growing AI & Machine Learning team. In this role, you’ll help … machine learning models that solve real-world problems — all while receiving hands-on training, mentoring, and support from experienced ML engineers and data scientists. Whether you studied Computer Science, Engineering, Data Science, or Maths — if you're passionate about machine learning, love to build, and eager to learn, this is the perfect opportunity to kickstart your career. What You … learning models using Python and ML frameworks like TensorFlow, PyTorch, or Scikit-learn Data Preparation : Work on collecting, cleaning, transforming, and analysing large datasets for training and testing models Feature Engineering : Support the design and selection of relevant input features to improve model performance Model Evaluation : Learn to test models for accuracy, robustness, and fairness using best practices More ❯

have an exciting opportunity for a Data Scientist to join our rapidly growing Sports Forecasting & Analytics company. Purpose of the role As a Data Scientist within the Modelling & Data Engineering department, you will play a key role in the design, development, and implementation of predictive models that power our sports forecasting products. You will work collaboratively within a sport … from large-scale sports datasets using sound mathematical and statistical principles. Translate modelling requirements and business objectives into effective data science solutions, working closely with the Delivery Manager and Engineering teammates (Software and Data Engineers) within your modelling team. Perform data cleaning, exploratory data analysis (EDA), feature engineering, and model evaluation to support continuous model improvement. Write … able to contribute to cross-functional discussions. Proven problem-solving and time management skills. Desirable: Familiarity with cloud services (e.g. AWS S3, Athena, Lambda). Basic understanding of data engineering or ML pipelines. Knowledge of distributed systems (e.g. Kafka). Interest in American sports or the betting industry. Some exposure to .NET-based systems or application integration. Follow our More ❯

have an exciting opportunity for a Data Scientist to join our rapidly growing Sports Forecasting & Analytics company. Purpose of the role As a Data Scientist within the Modelling & Data Engineering department, you will play a key role in the design, development, and implementation of predictive models that power our sports forecasting products. You will work collaboratively within a sport … from large-scale sports datasets using sound mathematical and statistical principles. Translate modelling requirements and business objectives into effective data science solutions, working closely with the Delivery Manager and Engineering teammates (Software and Data Engineers) within your modelling team. Perform data cleaning, exploratory data analysis (EDA), feature engineering, and model evaluation to support continuous model improvement. Write … able to contribute to cross-functional discussions. Proven problem-solving and time management skills. Desirable: Familiarity with cloud services (e.g. AWS S3, Athena, Lambda). Basic understanding of data engineering or ML pipelines. Knowledge of distributed systems (e.g. Kafka). Interest in American sports or the betting industry. Some exposure to .NET-based systems or application integration. Follow our More ❯

Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL and NoSQL databases Understanding of data preprocessing, feature engineering, and model deployment Experience with unit testing, CI/CD, and version control (Git) Strong problem-solving skills and attention to detail Preferred Qualifications: Experience in Natural … for AI model deployment Familiarity with containerization (Docker/Kubernetes) Experience with real-time data processing and analytics Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, AI, or related field Soft Skills: Strong communication and collaboration skills Ability to learn and adapt quickly in a fast-paced environment Critical thinking and analytical mindset Benefits: Competitive More ❯

Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL and NoSQL databases Understanding of data preprocessing, feature engineering, and model deployment Experience with unit testing, CI/CD, and version control (Git) Strong problem-solving skills and attention to detail Preferred Qualifications: Experience in Natural … for AI model deployment Familiarity with containerization (Docker/Kubernetes) Experience with real-time data processing and analytics Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, AI, or related field Soft Skills: Strong communication and collaboration skills Ability to learn and adapt quickly in a fast-paced environment Critical thinking and analytical mindset Benefits: Competitive More ❯

Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL and NoSQL databases Understanding of data preprocessing, feature engineering, and model deployment Experience with unit testing, CI/CD, and version control (Git) Strong problem-solving skills and attention to detail Preferred Qualifications: Experience in Natural … for AI model deployment Familiarity with containerization (Docker/Kubernetes) Experience with real-time data processing and analytics Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, AI, or related field Soft Skills: Strong communication and collaboration skills Ability to learn and adapt quickly in a fast-paced environment Critical thinking and analytical mindset Benefits: Competitive More ❯

Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL and NoSQL databases Understanding of data preprocessing, feature engineering, and model deployment Experience with unit testing, CI/CD, and version control (Git) Strong problem-solving skills and attention to detail Preferred Qualifications: Experience in Natural … for AI model deployment Familiarity with containerization (Docker/Kubernetes) Experience with real-time data processing and analytics Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, AI, or related field Soft Skills: Strong communication and collaboration skills Ability to learn and adapt quickly in a fast-paced environment Critical thinking and analytical mindset Benefits: Competitive More ❯

Key Skills Proficiency in Python and/or R for developing machine learning models. Experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn. Strong understanding of data preprocessing, feature engineering, and model evaluation techniques. Familiarity with cloud platforms like AWS, GCP, or Azure for deploying ML solutions. Knowledge of version control systems (e.g., Git) and CI/ More ❯

and product managers, to deliver robust AI solutions. Key Skills Proficiency in Python, TensorFlow, or PyTorch Experience with machine learning algorithms and frameworks Strong understanding of data pre-processing, feature engineering, and model evaluation Familiarity with cloud services (AWS, GCP, Azure) and their AI/ML offerings Knowledge of natural language processing (NLP) and computer vision is a More ❯

with and learn from team members while sharing your expertise in a growth-oriented environment The Superpowers You'll Be Bringing To The Team Academic background: Tertiary qualifications in engineering, mathematics, actuarial studies, statistics, physics, or a related discipline Technical experience: 2-5 years of commercial experience in data analytics or data science, demonstrating practical application of analytical techniques … Analytics knowledge: Solid understanding of data preparation, feature engineering, analytics concepts, model development and validation Coding experience: Proficient in Python/SQL with experience in similar analytical programming languages Healthcare experience: Experience working with healthcare or life sciences data and applying analytics to improve patient, clinician or customer outcomes Stakeholder engagement: Experience building trusted relationships with senior stakeholders More ❯