sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit youll use Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/CD, Docker, AWS (S3, Lambda More ❯
City of London, Greater London, UK Hybrid / WFH Options
Areti Group | B Corp
sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit youll use Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/CD, Docker, AWS (S3, Lambda More ❯
data science. Mandatory Skills Description: Minimum 8+ years of hands-on experience in Data Science with strong expertise in Python and libraries such as Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, or PyTorch. Proven ability to design, develop, and deploy machine learning, deep learning, and predictive models to solve complex business problems. Strong background in statistical analysis, data mining, and More ❯
inference. Requirements 5+ years in AI/ML engineering or applied research, with deep experience in LLMs, generative AI, or autonomous AI agents. Strong programming skills in Python, PyTorch, TensorFlow, or JAX. Hands-on experience with agentic AI, multi-step reasoning, and decision-making pipelines. Knowledge of RAG, vector databases, embeddings, and autonomous task orchestration. Experience deploying AI models More ❯
City of London, Greater London, UK Hybrid / WFH Options
Tenth Revolution Group
inference. Requirements 5+ years in AI/ML engineering or applied research, with deep experience in LLMs, generative AI, or autonomous AI agents. Strong programming skills in Python, PyTorch, TensorFlow, or JAX. Hands-on experience with agentic AI, multi-step reasoning, and decision-making pipelines. Knowledge of RAG, vector databases, embeddings, and autonomous task orchestration. Experience deploying AI models More ❯
models. Implement drift detection and model monitoring frameworks (experience with AgentEvals for LLMs is a plus). Key Skills: Proven experience in Chatbot Development using: Python, PyCharm, NumPy, Pandas TensorFlow/Deep Learning/NLP frameworks MySQL, PostgreSQL, NoSQL, RDBMS design & data modelling GitHub, Jenkins for CI/CD and version control Strong background in data modelling, wrangling, and More ❯
provisioning data infrastructure, including permissions, clusters, jobs, and lakehouse resources. Proven experience in building MLOps pipelines, tracking model lifecycle, and integrating with modern ML frameworks (e.g., scikit-learn, XGBoost, TensorFlow). Exposure to streaming data pipelines (e.g., Kafka, Structured Streaming) and real-time analytics architectures is a strong plus. Experience implementing robust DevOps practices for data engineering: versioning, testing More ❯
provisioning data infrastructure, including permissions, clusters, jobs, and lakehouse resources. Proven experience in building MLOps pipelines, tracking model lifecycle, and integrating with modern ML frameworks (e.g., scikit-learn, XGBoost, TensorFlow). Exposure to streaming data pipelines (e.g., Kafka, Structured Streaming) and real-time analytics architectures is a strong plus. Experience implementing robust DevOps practices for data engineering: versioning, testing More ❯
in LLM projects including training, fine-tuning, or production deployment Strong track record in scalable AI system development Technical Expertise Expert-level Python programming with deep knowledge of PyTorch, TensorFlow, or JAX Proven experience with distributed computing environments and modern MLOps workflows Practical knowledge of LLM toolkits (Hugging Face ecosystem, training frameworks) Strong problem-solving abilities for complex model More ❯
in LLM projects including training, fine-tuning, or production deployment Strong track record in scalable AI system development Technical Expertise Expert-level Python programming with deep knowledge of PyTorch, TensorFlow, or JAX Proven experience with distributed computing environments and modern MLOps workflows Practical knowledge of LLM toolkits (Hugging Face ecosystem, training frameworks) Strong problem-solving abilities for complex model More ❯
from structured and unstructured data. Build data pipelines, models, and AI applications using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with More ❯
City of London, Greater London, UK Hybrid / WFH Options
Deloitte
from structured and unstructured data. Build data pipelines, models, and AI applications using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with More ❯
or a similar role, preferably within the finance industry or at a leading technology company. Strong expertise in algorithms, data structures, multivariate calculus, and linear algebra. Proficient in Python, TensorFlow, PyTorch, or similar languages and frameworks, with experience writing CUDA kernels and profiling GPU code a plus. Excellent communication skills, with the ability to work effectively in cross-functional More ❯
knowledge of ML/statistical methods (e.g. supervised/unsupervised, Bayesian, time-series). Strong Python skills with core libraries (NumPy, Pandas, Scikit-Learn) plus deep learning frameworks (PyTorch, TensorFlow). Strong leadership in project delivery, architecture, and technical decision-making. Excellent communicator, able to simplify complex ideas for any audience. Strategic thinker with awareness of FS sector trends. More ❯
knowledge of ML/statistical methods (e.g. supervised/unsupervised, Bayesian, time-series). Strong Python skills with core libraries (NumPy, Pandas, Scikit-Learn) plus deep learning frameworks (PyTorch, TensorFlow). Strong leadership in project delivery, architecture, and technical decision-making. Excellent communicator, able to simplify complex ideas for any audience. Strategic thinker with awareness of FS sector trends. More ❯
/AI (LLMs, data mining, recommendation systems, or pattern recognition) Proven hands-on experience with LLM agents and generative AI systems Strong Python skills, with experience in PyTorch or TensorFlow Familiarity with agentic design principles and LLaMA-based architectures Advanced debugging & problem-solving ability Experience running large-scale ML experiments and managing compute environments Masters (or PhD) in Computer More ❯
Data Scientist/Data Engineer A understand of Palantir would be a huge + Experience of completing projects to deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL More ❯
or Engineering Experience building and deploying ML models into production (e.g., in forecasting, optimisation, or computer vision) Proficiency in Python and familiarity with key ML libraries like Scikit-learn, TensorFlow, or PyTorch Solid foundation in statistical modelling and machine learning techniques Exposure to cloud technologies such as AWS, especially services like SageMaker or Lambda, is a bonus Comfortable collaborating More ❯
or Engineering Experience building and deploying ML models into production (e.g., in forecasting, optimisation, or computer vision) Proficiency in Python and familiarity with key ML libraries like Scikit-learn, TensorFlow, or PyTorch Solid foundation in statistical modelling and machine learning techniques Exposure to cloud technologies such as AWS, especially services like SageMaker or Lambda, is a bonus Comfortable collaborating More ❯
Have: Previous experience as a Data Scientist or Data Engineer Strong command of Python (including libraries such as scikit-learn, NumPy, matplotlib) Experience in deep learning frameworks such as TensorFlow or PyTorch Knowledge of SQL and relational databases; experience with Big Data environments Familiarity with API development and NoSQL databases Understanding of CI/CD practices , AWS , and GIT More ❯
Have: Previous experience as a Data Scientist or Data Engineer Strong command of Python (including libraries such as scikit-learn, NumPy, matplotlib) Experience in deep learning frameworks such as TensorFlow or PyTorch Knowledge of SQL and relational databases; experience with Big Data environments Familiarity with API development and NoSQL databases Understanding of CI/CD practices , AWS , and GIT More ❯
deployment hurdles. Ability to translate business questions into analytical frameworks and interpret results for non-technical stakeholders. Strong proficiency in Python, SQL, and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch). Experience with model operationalization using tools like Docker, Kubernetes, MLflow, or SageMaker. Marketing KPIs knowledge: CTR, conversion rate, MQL to SQL, ROI, CLV, CAC, retention. Experience working … Prophet, or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy, matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data Access & Engineering Collaboration : Comfort working with cloud data warehouses (e.g., Snowflake More ❯
is highly preferred Demonstrated ability to deploy production-level ML modelsparticularly in optimisation, demand forecasting, or computer vision Advanced proficiency in Python and ML frameworks such as Scikit-learn, TensorFlow, or PyTorch Solid understanding of supervised and unsupervised learning, statistical modelling, and mathematical optimisation Hands-on experience with AWS services, especially SageMaker, Lambda, and related infrastructure Willingness to contribute More ❯
is highly preferred Demonstrated ability to deploy production-level ML modelsparticularly in optimisation, demand forecasting, or computer vision Advanced proficiency in Python and ML frameworks such as Scikit-learn, TensorFlow, or PyTorch Solid understanding of supervised and unsupervised learning, statistical modelling, and mathematical optimisation Hands-on experience with AWS services, especially SageMaker, Lambda, and related infrastructure Willingness to contribute More ❯
