London, South East, England, United Kingdom Hybrid / WFH Options
Opus Recruitment Solutions Ltd
world use cases Contribute to code reviews, testing, and documentation Required Skills & Experience Strong proficiency in Python and its AI/ML ecosystem (e.g. NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow) Experience with machine learning model development , training, and deployment Familiarity with LLMs , NLP , or computer vision techniques Solid understanding of software engineering principles and version control (Git) Experience working More ❯
Manchester, Lancashire, England, United Kingdom Hybrid / WFH Options
Adria Solutions
the team. Skills and Experience: Degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Proficiency in Python and key libraries such as NumPy, Pandas, scikit-learn, TensorFlow or PyTorch. Basic understanding of machine learning algorithms and model evaluation techniques. Strong analytical and communication skills. Comfortable working in a collaborative environment and taking feedback. Desirable: MSc in More ❯
practices in machine learning. Optimization : Continuously improve machine learning infrastructure and production workflows. Strong technical foundation in machine learning and software engineering Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn) Experience with cloud platforms (AWS, GCP, Azure) Experience with CI/CD pipelines for machine learning (e.g., Vertex AI) Familiarity with data processing tools like Apache More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Method Resourcing
core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed data More ❯
versioning Exposure to tools like KServe, Ray Serve, Triton, or vLLM is a big plus Bonus Points Experience with observability frameworks like Prometheus or OpenTelemetry Knowledge of ML libraries: TensorFlow, PyTorch, HuggingFace Exposure to Azure or GCP Passion for financial services Qualifications Degree in Computer Science, Engineering, Data Science, or similar What We Offer A collaborative and innovative work More ❯
developing underwriting or behavioural models for credit extension Desired: Master's degree in data science/Machine Learning or related discipline Knowledge of Deep Learning frameworks, ideally Keras/Tensorflow Familiarity with software version control (GitHub, bitbucket) Knowledge of Tableau Ability to comprehend research papers and possibly apply their solutions Credit card industry knowledge What's in it for More ❯
mentoring junior engineers or data scientists and fostering a collaborative, growth-oriented culture. Preferred Qualifications: AWS Machine Learning Specialty certification or equivalent. Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras. Familiarity with big data tools like Spark, Kafka, or Hadoop. Understanding of MLOps principles, including model monitoring, drift detection, and CI/CD for ML. Exposure More ❯
software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow) Distributed computing frameworks (e.g., Spark, Dask) Cloud platforms (e.g., AWS, Azure, GCP) and HP computing Containerization and orchestration (Docker, Kubernetes) Strong problem-solving skills and the ability to More ❯
learning, and business analytics Hands-on experience with ML techniques such as XGBoost, deep neural networks, and transformers Practical knowledge of ML libraries and frameworks such as Fastai, Keras, TensorFlow, PyTorch, and Scikit-learn Ability to research, understand, and apply emerging machine learning techniques Programming & Data Engineering Proficiency in programming languages such as Python (preferred) and C++ Experience working More ❯
core software tooling: Git, Unix/Linux, Docker. Plus, a strong opinion on your IDE/editor of choice is welcome Familiarity with modern machine learning tools, for instance TensorFlow, Keras, PyTorch or SKLearn. Commercial experience with these is not essential. Excellent communication skills; both in customer-facing and internal team communication. Knowledge of MLOps is not essential, but More ❯
with 6 years, or PhD with 4 years Proficiency in data science languages and tools (e.g., Python, R, SQL, Jupyter, Pandas, Scikit-learn) Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and big data platforms (e.g., Spark, Hadoop) Strong background in statistics, data modeling, and algorithm development Ability to explain complex data findings to technical and non-technical stakeholders More ❯
Science (or related field). 3+ years of experience writing production-grade Python code. 3+ years of hands-on experience with core Python data libraries (e.g., pandas, numpy, sklearn, tensorflow, pytorch, matplotlib). At least 1 year of experience deploying machine learning models in production environments. 1-2 years of experience working with SQL/NoSQL databases (e.g., Elasticsearch More ❯
monitoring frameworks Participate in code reviews, design discussions, and performance tuning Requirements: 3+ years of experience in a Machine Learning Engineer or similar role Proficiency in Python , ML frameworks (TensorFlow, PyTorch), and deployment tools (Docker, MLflow, etc.) Experience building scalable ML pipelines in cloud environments (AWS, GCP or Azure) Familiarity with energy systems, smart metering, or IoT data is More ❯
Learning, Computer Science, Engineering, Statistics, or equivalent fields • Strong mathematical background (linear algebra, calculus, probability & statistics) • Experience with machine learning model training and analysis through open-source frameworks (Pytorch, Tensorflow, Sklearn) • Experience crafting, conducting, analyzing, and interpreting experiments and investigations. • Experience with modern software development tools and practices (Git, pull requests) • Experience analyzing model performance with relevant metrics and More ❯
developing underwriting or behavioural models for credit extension Desired: Master's degree in Data Science/Machine Learning or related discipline Knowledge of Deep Learning frameworks, ideally Keras/Tensorflow Familiarity with software version control (GitHub, bitbucket) Knowledge of Tableau Ability to comprehend research papers and possibly apply their solutions Credit card industry knowledge What's in it for More ❯
platforms, and retrieval-augmented generation systems. Qualifications: 3+ years of experience delivering full-stack AI/ML applications in production. Proficiency in Python, especially with ML libraries such as TensorFlow, PyTorch, scikit-learn, and backend frameworks like FastAPI, Django, Flask. Experience with frontend frameworks: React, Vue, or Angular. Hands-on experience building and scaling ML models (LLMs, NLP, classification More ❯
meet deadlines, and deliver on project objectives. Masters degree in a STEM field (maths, science, engineering etc.) or equivalent Strong programming skills in Python (e.g., NumPy, Pandas, scikit-learn, TensorFlow/PyTorch). Demonstrable experience in creating and developing Python libraries. Demonstrable experience designing, implementing and training machine learning models from scratch. Strong foundations in applied mathematics and physics More ❯
with the Model Risk Management (MRM) lifecycle, including model documentation, testing, validation, and alignment with governance and compliance frameworks. Proficiency in Pythonand tools such as LangChain, Pandas, PyTorch/TensorFlow, and FastAPI. Strong understanding of prompt engineering, RAG pipelines, vector databases (e.g., FAISS, Chroma), and LLM evaluation strategies. Familiarity with software engineering best practices, including: REST API design and More ❯
on NLP and AI Advanced and hands on experience using: Python, Databricks, Azure ML, Azure Cognitive Service, Ads Data Hub, BIQuery, SAS, R, SQL, PySpark, Numpy, Pandas, Scikit Learn, TensorFlow, PyTorch, AutoTS, Prophet, NLTK Experience with Azure Cloud technologies including Azure DevOps, Azure Synapse, MLOps, GitHub Solid experience working with large datasets and developing ML/AI systems such More ❯
Own critical platform components from conception through production deployment Who You Are Expert proficiency in Python, JavaScript, and modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation More ❯
Own critical platform components from conception through production deployment Who You Are Expert proficiency in Python, JavaScript, and modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation More ❯
effectively across departments and navigate large organisations. Strong project management and organizational skills. Proficiency in programming languages such as Python, Java and Scala, and experience with ML frameworks like TensorFlow, PyTorch, and scikit-learn. Experience with cloud platforms (e.g., AWS), big data technologies (e.g., Spark) as well as other technologies used to deploy models to production (e.g., Kubernetes, GHA More ❯
are looking for: Essential: UK SC Clearance or the ability obtain it Demonstrable experience developing a variety of machine learning models Strong grasp of machine learning frameworks (e.g. PyTorch, Tensorflow) Knowledge of machine learning architectures, loss functions, tools and techniques Experience training machine learning models, including hyperparameter tuning and optimizing model performance Experience with (or at least exposure to More ❯
