related field. 7+ years of professional software development experience, with at least 3 years in AI/ML. Strong proficiency in Python , including libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch . Solid understanding of ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . Hands-on More ❯
on experience in developing and deploying machine learning models in a production environment. Strong programming skills in Python and experience with relevant machine learning libraries and frameworks such as TensorFlow, Keras, PyTorch, scikit-learn, etc. Solid understanding of machine learning algorithms (e.g., regression, classification, clusting, dimensionality reduction, deep learning architectures). Experience with data preprocessing, feature engineering, and data More ❯
learning algorithms and their practical applications, particularly in fraud prevention and user personalization. Experience designing, developing, and implementing advanced machine learning models. Familiarity with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn. Data Engineering Skills: Proficiency in developing and maintaining real-time data pipelines for processing large-scale data. Experience with ETL processes for data ingestion and More ❯
developing and deploying AI/ML models in a production environment. Proficiency in programming languages such as Python, Java, or C++. Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Familiarity with data processing tools and platforms (e.g., SQL, Apache Spark, Hadoop). Knowledge of cloud computing services (e.g., AWS, Google Cloud, Azure) and containerization More ❯
see from you: Strong understanding of a wide range of ML algorithms. Understanding of MLOps practices for managing and monitoring models in production. Experience with deep learning frameworks (e.g. TensorFlow, PyTorch). Proficiency in programming languages such as Python, SQL and R. Knowledge of SQL and NoSQL databases for data storage and retrieval. Experience with LLM application design and More ❯
practices. Diagnose and resolve complex technical challenges in big data and ML systems. About You You're fluent in Python and experienced with leading ML/AI frameworks (PyTorch, TensorFlow, Scikit-learn, Hugging Face). You have a solid background in MLOps: experiment tracking, CI/CD for ML, model versioning, deployment, and monitoring. You've built scalable backend More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Intellect Group
and collaboration skills Full right to work in the UK (we are unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits More ❯
and collaboration skills Full right to work in the UK (we are unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits More ❯
Skills and Qualifications Skills & Expertise Strong experience in machine learning, deep learning, and statistical analysis. Expertise in Python, with proficiency in ML and NLP libraries such as Scikit-learn, TensorFlow, Faiss, LangChain, Transformers and PyTorch. Experience with big data tools such as Hadoop, Spark, and Hive. Familiarity with CI/CD and MLOps frameworks for building end-to-end More ❯
journey mapping, conversion optimization, and media effectiveness. Proficiency in Python with extensive experience in data science libraries (e.g.scikit-learn, pandas, NumPy, SciPy, etc) Experience with ML frameworks such as TensorFlow, PyTorch, XGBoost, LightGBM, or similar Strong SQL skills and experience with data warehousing solutions (Snowflake, BigQuery, Redshift) Experience with cloud platforms (AWS, Azure, GCP) and their ML and AI More ❯
models in production environments Continuously optimise models based on real-world feedback Maintain clear documentation for workflows and models Required Skills: Strong Python skills + ML libraries (scikit-learn, TensorFlow, PyTorch) Solid understanding of data preprocessing & feature engineering Knowledge of supervised, unsupervised, and deep learning methods Experience in model evaluation & tuning Familiarity with AWS, GCP, or Azure is a More ❯
with 3+ years of demonstrated and related industry experience Strong programming skills in languages such as Python, Java, and/or R. Experience with machine learning frameworks such as TensorFlow, Keras, and/or PyTorch. Solid understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning), deep learning, and neural networks. Experience with data preprocessing, feature engineering, and model evaluation More ❯
with cloud infrastructure Experience with graph technology and/or algorithms Our technology stack Python and associated ML/DS libraries (Scikit-learn, Numpy, LightlGBM, Pandas, LangChain/LangGraph, TensorFlow, etc...) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc. MLOps: Terraform, Docker, Airflow, MLFlow More Information Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad More ❯
with a strong portfolio of high-impact projects in production Expert-level programming skills in Python and SQL, and fluency with leading ML/AI frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Direct experience with GenAI/LLM technologies, including tools like Hugging Face, LangChain, OpenAI APIs, vector databases, and fine-tuning methods Deep knowledge of machine learning algorithms (supervised More ❯
to image recognition applications and LLM-based chatbots and agents Proven ability to build machine learning models and pipelines using Python and common ML and DL libraries (e.g. Pytorch, Tensorflow) from early conceptualisation to full deployment in scalable production environments Ability to design, deploy and maintain ML solutions on modern frameworks to meet functional business requirements, adhering to software More ❯
Bricks/Data QISQL for data access and processing (PostgreSQL preferred, but general SQL knowledge is important) Latest Data Science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g., TensorFlow, MXNet, scikit-learn) Software engineering practices (coding standards, unit testing, version control, code review) Hadoop distributions (Cloudera, Hortonworks), NoSQL databases (Neo4j, Elastic), streaming technologies (Spark Streaming) Data manipulation and More ❯
and continuous integration Requirements: 3+ years of experience in software engineering, with a focus on AI/ML integration Proficiency in Python and ML frameworks such as PyTorch or TensorFlow Strong grasp of software architecture and microservices Experience working in containerised environments (Docker, Kubernetes) Familiarity with CI/CD pipelines, secure deployment practices and cloud deployment (e.g., AWS/ More ❯
the lifecycle of ML projects, including initial conceptualization, data handling, model development, and deployment. Proficiency in programming languages, including Python. Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-Learn, etc. Experience developing Python APIs using tools such as FastAPI. Knowledge of database technologies (SQL, MongoDB, Databricks) and data pipeline tools. Familiar with ML CI/ More ❯
advancements in AI/ML, LLMs, and GenAI technologies. To Be Successful in The Role, You Will Have Required Skills: Proficiency in Python and machine learning framework s (e.g., TensorFlow, PyTorch, Scikit-Learn). Hands-on experience with OpenAI APIs and Microsoft Azure AI services. Strong understanding of large language models, prompt engineering, and fine-tuning techniques. Experience with More ❯
machine learning modelling techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they emerge. Experience of using More ❯
world applications, especially in NLP or classification problems Data Engineering: Experience with data pipeline development, ETL processes, and working with large datasets Hands on experience with ML tools like TensorFlow, PyTorch etc. Experience with Azure cloud (AKS, Azure AI, ADF, Document Intelligence etc.) Excellent problem-solving skills and software engineering practices Excellent communication skills Preferred Qualifications & Skills: If you More ❯
depth knowledge and familiarity with cloud platforms like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Technical Skills Good to have: Expertise in any one framework (TensorFlow, Pytorch, Keras) Experience in a statistical programming language (e.g. R or Python) and applied machine learning and AI techniques (i.e computer vision, deep learning, conversational AI, and natural language More ❯
Northern Virginia with occasional travel to client sites. A degree in Computer Science or a related field. 3+ years of hands-on experience with Python coding (pandas, numpy, sklearn, TensorFlow, PyTorch, etc.). Proven experience deploying machine learning models into production environments. Proficiency with SQL/NoSQL databases, version control tools (e.g., Git), Docker, and Kubernetes. Strong ownership, accountability More ❯