london (city of london), south east england, united kingdom Hybrid / WFH Options
Datatech Analytics
and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross More β―
slough, south east england, united kingdom Hybrid / WFH Options
Datatech Analytics
and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross More β―
experience working as a Data Scientist or Machine Learning Engineer in a commercial setting. Strong programming skills in Python, with hands-on experience using libraries such as Pandas, Scikit-Learn, Jupyter, and Matplotlib. Proficient in SQL for data extraction and transformation. Experience with Google Cloud Platform (GCP) and Vertex AI for developing and deploying ML services is highly More β―
london, south east england, united kingdom Hybrid / WFH Options
ea Change
technical audiences Right to work in the UK Strong academic background (GCSEs, A-Levels or equivalent) Desirable (but not essential) Experience with Python libraries like Pandas, NumPy, or Scikit-learn Exposure to machine learning concepts or blockchain architecture Coursework or personal projects involving data analysis, AI/ML, or distributed systems Knowledge of data visualisation tools like Power More β―
London, South East, England, United Kingdom Hybrid / WFH Options
Sanderson
ML issues in live production environments. We're looking for individuals with: Experience: Proven background as a Machine Learning Engineer. Technical Skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib). Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex AI (developing ML services). Expertise: Solid understanding of computer More β―
and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research More β―
london (city of london), south east england, united kingdom
Safe Intelligence
and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research More β―
and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research More β―
London, South East, England, United Kingdom Hybrid / WFH Options
Robert Half
What We're Looking For A Bachelor's degree in Computer Science, Mathematics, Electrical Engineering, or a related field. Strong experience with Python and data science libraries (Pandas, Scikit-learn, etc.). Solid understanding of machine learning concepts and algorithms . Interest in working with real-world industrial or sensor data . Exposure to Apache Airflow and/ More β―
a senior data science role. Deep understanding of machine learning model lifecycles and optimisation. Skilled in building, training, and deploying models on large datasets. Proficiency in Python, PyTorch, Scikit-learn, and similar ML frameworks. Experience with cloud environments (AWS preferred), containerisation, and modern data infrastructure. Excellent communication skills, with the ability to work effectively across technical and non More β―
a senior data science role. Deep understanding of machine learning model lifecycles and optimisation. Skilled in building, training, and deploying models on large datasets. Proficiency in Python, PyTorch, Scikit-learn, and similar ML frameworks. Experience with cloud environments (AWS preferred), containerisation, and modern data infrastructure. Excellent communication skills, with the ability to work effectively across technical and non More β―
NumPy, Pandas, SciPy) β’ SQL or time-series DBs β’ Linux & distributed systems expertise β’ Strong communication & market intuition β¨ Bonus Skills β’ KDB+/Q, Haskell, or other functional languages β’ Machine learning (scikit-learn, etc.) β’ Quant tools & mathematical background β’ Docker, Kubernetes, AWS π Location : London (1 remote day per week) πΌ Type : Full-time | Competitive comp + performance bonus Ready to build systems that More β―
NumPy, Pandas, SciPy) β’ SQL or time-series DBs β’ Linux & distributed systems expertise β’ Strong communication & market intuition β¨ Bonus Skills β’ KDB+/Q, Haskell, or other functional languages β’ Machine learning (scikit-learn, etc.) β’ Quant tools & mathematical background β’ Docker, Kubernetes, AWS π Location : London (1 remote day per week) πΌ Type : Full-time | Competitive comp + performance bonus Ready to build systems that More β―
london (city of london), south east england, united kingdom
Bruin
NumPy, Pandas, SciPy) β’ SQL or time-series DBs β’ Linux & distributed systems expertise β’ Strong communication & market intuition β¨ Bonus Skills β’ KDB+/Q, Haskell, or other functional languages β’ Machine learning (scikit-learn, etc.) β’ Quant tools & mathematical background β’ Docker, Kubernetes, AWS π Location : London (1 remote day per week) πΌ Type : Full-time | Competitive comp + performance bonus Ready to build systems that More β―
Azure AI Services). Experience with a major conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: Working with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and More β―
to stochastic optimisation models. What skills, experience and qualities are we looking for? Python - demonstrable experience required Experience working across a range of ML models, e.g. TensorFlow and scikit-learn Significant experience in the energy industry, with a specific focus on forecasting the short-term power markets GitHub or Azure DevOps knowledge is desired SQL knowledge is desired More β―
evaluation Experience in SQL and Python for advance analytics and modelling (experience with Snowflake, R, GitHub, and Jira is a plus) Experience using Python libraries such as pandas, scikit-learn, and statsmodels (or R equivalent) Experience using BI tools like Power BI or Tableau to communicate insights Experience mentoring or upskilling colleagues in analytics tools (such as SQL More β―
knowledge of running cost-effective serverless architecture. Experience working with Python, C#, and Angular. Strong interpersonal, communication, and presentation skills applicable to a wide audience. Experience with PyTorch, Scikit-learn, Go, Databricks, JavaScript, and Azure Pipelines is desirable, but not essential. Experience in leading software engineering efforts for AI-enabled SaaS products is desirable, but not essential. Why More β―
or desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as More β―
london (city of london), south east england, united kingdom
Safe Intelligence
or desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as More β―
or desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as More β―
operational challenges. Hands-on expertise with cloud platforms (AWS, Azure, Google Cloud) and scalable, secure data infrastructures. Skilled in analytics, problem-solving, and applying machine learning (TensorFlow, PyTorch, Scikit-learn) to business use cases. Excellent communication and stakeholder management, comfortable engaging with C-level executives. Please note that this role does not offer visa sponsorship If youβre More β―