Modelling Approaches: Machine learning, optimisation, stochastic and agent-based models About You Experience in the energy sector - markets, trading, forecasting, etc. Strong Python skills with machine learning frameworks (scikit-learn, TensorFlow, PyTorch). Knowledge of GitHub/Azure DevOps and SQL advantageous. Excellent communicator, able to explain technical concepts to non-technical audiences. Degree (or equivalent experience) in More ❯
building RAG pipelines, and experimenting with agentic AI workflows. Strong Python development skills and familiarity with modern ML and NLP frameworks and tooling (e.g. Hugging Face, spaCy, PyTorch, Scikit-learn). Familiarity with Kubernetes and infrastructure for deploying and scaling ML models is a plus. Exposure to systems integration challenges (e.g. connecting ML workflows with data stores like More ❯
Reading, Berkshire, South East, United Kingdom Hybrid / WFH Options
Queen Square Recruitment Limited
algorithms, and frameworks . Proficiency in programming languages (Python, R, C/C++, Java) and secure coding practices. Hands-on experience with ML/LLM frameworks (TensorFlow, PyTorch, scikit-learn, etc.). Expertise in DevOps/CI/CD security and cloud-native architectures (containers, Kubernetes, Git). Strong knowledge of AI/ML-specific security vulnerabilities (adversarial More ❯
you want to understand why they work You follow best practices by default , and know when it's time to question them Your Tools Python - comfy with pandas, scikit-learn & friends Data Science basics - from feature engineering to model validation SQL - joins, aggregations, subqueries? No problem Docker & Linux - smooth setup and deployment AI/ML - real models, not More ❯
you want to understand why they work You follow best practices by default , and know when it's time to question them Your Tools Python - comfy with pandas, scikit-learn & friends Data Science basics - from feature engineering to model validation SQL - joins, aggregations, subqueries? No problem Docker & Linux - smooth setup and deployment AI/ML - real models, not More ❯
you want to understand why they work You follow best practices by default , and know when it's time to question them Your Tools Python - comfy with pandas, scikit-learn & friends Data Science basics - from feature engineering to model validation SQL - joins, aggregations, subqueries? No problem Docker & Linux - smooth setup and deployment AI/ML - real models, not More ❯
10+ years of experience Expert-level FastAPI development for building scalable APIs Proficiency with async/await patterns and concurrent programming Experience with Python ML libraries (NumPy, Pandas, scikit-learn) Knowledge of testing frameworks (pytest, unittest) and CI/CD practices Cloud & Infrastructure Hands-on experience with Google Cloud Platform (GCP) Proficiency with containerization (Docker) and orchestration (Kubernetes More ❯
Spectrum, even better. You’ll need a Master’s or PhD in a quantitative field, strong Python skills, and extensive experience applying core machine learning libraries such as Scikit-learn, XGBoost, or LightGBM to structured data problems. The role may also involve developing and deploying deep learning models using frameworks like PyTorch or TensorFlow where appropriate. Experience with More ❯
Python or related language - Experience with neural deep learning methods and machine learning - Experience with prompting techniques for LLMs PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. - PhD in math/statistics/engineering or other equivalent More ❯
of key machine learning models, including Gradient Boosting Machines (GBMs), Neural Networks and Large language models (LLMs). Hands-on experience with popular machine learning libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Knowledge of AWS products and services including Sagemaker. Deep knowledge of Microsoft Excel in a commercial setting. You enjoy being Agile - you should More ❯
junior team members, and collaborating closely with engineers, PMs and analysts to deliver measurable user and business impact. We work primarily in Python and SQL, with tools like Scikit-learn, Tensorflow, PyTorch and Pandas. Our ML stack runs on AWS and Sagemaker. We value clean, documented, well-tested and reviewed code-and have the tooling and culture to More ❯
We are seeking a skilled AI Developer with a strong focus on building and integrating artificial intelligence solutions within web applications. The candidate must have hands-on experience in developing intelligent features, leveraging machine learning models, natural language processing (NLP More ❯
LLM security, and synthetic data misuse. Collaborate with data science, security, and legal teams on AI compliance and ethics. Required Skills: Hands-on expertise in TensorFlow, PyTorch, and Scikit-learn with a focus on security testing. Strong understanding of adversarial ML attack/defense strategies. Knowledge of federated learning, differential privacy, and secure multiparty computation (SMPC). Familiarity More ❯
In regard to you…it would be great if you bring strong Python skills, experience with Azure ML, Docker, Git, and a passion for machine learning tools like scikit-learn, TensorFlow or PyTorch. Bonus points if you're curious about GenAI and know your way around SQL. If you're ready to build things that actually get used More ❯
Employment Type: Permanent
Salary: £65000 - £70000/annum up to £68k base + Bonus & awesome be
Central London, London, England, United Kingdom Hybrid / WFH Options
hireful
benefits! In regard to you...it would be great if you bring strong Python skills, experience with Azure ML, Docker, Git, and a passion for machine learning tools like scikit-learn, TensorFlow or PyTorch. Bonus points if you're curious about GenAI and know your way around SQL. If you're ready to build things that actually get used More ❯
on areas such as robustness, explainability, or uncertainty estimation. Advanced programming and mathematical skills with Python and an experience with the standard Python data science stack (NumPy, pandas, Scikit-learn etc.). The ability to conduct and oversee complex technical research projects. A passion for leading and developing technical teams; adopting a caring attitude towards the personal and More ❯
the-art areas (e.g. NLP, Transfer Learning) and modern Deep Learning algorithms (e.g. BERT, LSTM) Solid knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit-Learn, Matplotlib, etc.) Understanding of model evaluation, data pre-processing techniques (standardisation, normalisation, handling missing data) Solid understanding of statistics; hypothesis testing, probability distributions, sampling techniques Private Health Care More ❯
or journals - Strong analytical, mathematical, and coding skills (e.g., Python, C++, or Java) - Previous work on agents or LLMs PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. Amazon is an equal opportunity employer and does not discriminate More ❯
experience - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. Amazon is an equal opportunity employer and does not discriminate More ❯
in machine learning techniques (supervised, unsupervised, reinforcement learning) and deep learning architectures (CNNs, RNNs, Transformers). Strong in Python (required); experience with ML libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras. Working knowledge of cloud-native AI/ML services on AWS, Azure, or Google Cloud (e.g., SageMaker, Azure ML, Vertex AI). Understanding of AI red More ❯
monitoring and improvement). In-depth knowledge of statistical hypothesis testing and ML modeling techniques. Experience in using Python for numerical/statistical programming (including Numpy, Pandas, and Scikit-learn). Significant experience in using SQL. Ability to communicate effectively with audiences of various backgrounds, levels, and functions. Experience in conducting and analyzing AB tests in an e More ❯
with front-end web development frameworks such as Flask. • Demonstrated experience creating machine learning models that conduct text classification and topic modeling in Python using standard machine learning (SciKitLearn-) or deep learning models. • Demonstrated experience developing applications for semantic search. • Demonstrated professional or academic experience and proficiency with Tableau to produce visualizations and dashboards. • Demonstrated academic or More ❯
AI assurance by identifying and documenting model limitations and risks. Essential Skills & Experience Proficient in Python with a strong command of data science libraries such as pandas, NumPy, scikit-learn, and similar tools. Experience designing experiments and validating machine learning models with appropriate statistical rigor. Deep understanding of machine learning performance metrics and statistical evaluation techniques. Knowledge of More ❯
with: 3–5 years’ experience in a Data Science, AI, or ML-related role Experience with forecasting, propensity and segmentation Strong Python skills and experience with libraries like scikit-learn, pandas, and Prophet Hands-on experience developing and deploying ML models in production A track record of working across the full ML lifecycle in a fast-paced environment More ❯
