record of building and deploying ML models into production. Prior experience leading projects or teams is a plus for a lead role Programming & ML Skills: Advanced programming skills in Python (including libraries such as pandas, scikit-learn, TensorFlow/PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data More ❯
background with Windows and Linux operating systems Virtualisation (VMware, Hyper-V) and containerisation (Kubernetes, Docker) Solid understanding of networking (TCP/IP, DNS, DHCP, firewalls) Automation & Scripting (PowerShell, Bash, Python, Ansible, Terraform) Knowledge of cyber security controls and accreditation frameworks Experience across the systems engineering lifecycle Desirable: Cloud expertise (AWS, Azure) & Infrastructure as Code (Terraform, CloudFormation) Experience with enterprise integrations More ❯
related quantitative field. Essential Criteria Proven experience building and maintaining large-scale data pipelines using tools such as Databricks, Azure Data Factory, Snowflake, or similar Strong programming skills in Python and SQL, with proficiency in data engineering libraries (pandas, PySpark, dbt). Deep understanding of data modelling, ETL/ELT processes, and Lakehouse concepts. Experience with data quality frameworks, data More ❯
and training data. Implements best practices for the machine learning lifecycle, including model versioning, CI/CD, containerization (Docker), orchestration (Kubernetes), and automated monitoring. Demonstrates excellent programming skills in Python and other relevant languages, with a solid foundation in software engineering principles for building production-grade systems. Applies knowledge of governance, security, and compliance requirements to ensure responsible and ethical More ❯
solutions Windows and Linux operating systems Virtualisation platforms (VMware, Hyper-V) and containerisation (Kubernetes, Docker) Networking concepts (TCP/IP, DNS, DHCP, firewalls) Automation and scripting (e.g. PowerShell, Bash, Python, Ansible, Terraform) Knowledge of cybersecurity controls and accreditation requirements Expertise with cloud platforms (AWS, Azure) and Infrastructure as Code (CloudFormation, Terraform) Experience integrating enterprise services (Active Directory, PKI, monitoring, SIEM More ❯
experience in MLOps, DevOps, or related roles, focusing on ML and AI. Proven expertise in deploying and managing Generative AI models (e.g., GPT, Stable Diffusion, BERT). Proficient in Python and ML libraries such as TensorFlow, PyTorch, or Hugging Face. Skilled in cloud platforms (AWS, GCP, Azure) and managed AI/ML services. Hands-on experience with Docker, Kubernetes, and More ❯
a programming and application system environment, with solid experience and a working knowledge in the following technologies: OS: Linux, Windows Automation: Terraform, Chef, Jenkins, Ansible Cloud: AWS, Azure Scripting: Python, Groovy, PowerShell, Perl, Shell Scripts DevOps Tools: Jenkins, CI/CD, JFrog, Gits, Datadog, Splunk We are dedicated to fostering a collaborative, engaging, and inclusive environment and are committed to More ❯
teams to expand platform capabilities and improve reliability Engineer cloud-based solutions leveraging containerisation and infrastructure-as-code to support scalable ML systems Skills & Experience Strong programming background in Python (and/or C++) Proven experience with CI/CD systems, Git workflows, and infrastructure-as-code tooling Hands-on expertise with Azure Databricks and cloud-native technologies (Docker, Kubernetes More ❯
Proven experience (7+ years) in data engineering. Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Technical skills: Advanced proficiency in SQL and Python for data manipulation and analysis Experience in Google data infrastructure, including DataPlex, DataCatalog and BigQuery Experience in Google data processing, including DataStream, DataFlow, Cloud Composer Experience building and maintaining data More ❯
will bring something new to the table! Required Minimum of five (5) years of experience as a software engineer developing internal tools and automating workflows at scale Proficiency in Python (or another scripting language) for development, testing, and automation of security and infrastructure workflows Hands-on experience applying AI/ML models, including LLMs, to automate complex business or security More ❯
such as content generation, technical Q&A, and call summarisation. Understanding of how AI augments human capabilities in sales and presales. Programming & Scripting Languages: Proficiency in languages such as Python or R, with strong knowledge of relevant libraries for data manipulation, scripting, and custom solution development. Experience with SQL for complex queries and data extraction. Cloud Architecture & Data Management: Strong More ❯
Need Essential: Expert knowledge of Postgres, including experience with large, distributed estates Strong SQL skills and the ability to diagnose and optimise performance bottlenecks Competence with automation tools (PowerShell, Python or similar) Hands-on experience supporting production environments and mission-critical systems Strong understanding of High Availability and Disaster Recovery technologies and database security Excellent communication skills and the ability More ❯
Hybrid Description Role Description We are seeking a Senior Software Developer with a strong focus on developing production-grade software, extensive experience with Azure services, and proficiency in Java, Python, PySpark. You will manage a team and collaborate with a third-party vendor to deliver robust, scalable solutions. Role Responsibilities Owning the development team in design, development, coding, testing. Managing More ❯
a practical understanding of modern DevOps toolchains and iterative delivery approaches. You should have: Hands-on experience with Kubernetes and Linux-based platform engineering. Strong scripting and automation capability (Python preferred). Familiarity with AWS, Azure, GCP or secure on-prem cloud equivalents. Solid understanding of networking concepts (routing, DNS, firewalls, service mesh). Experience with Elastic for monitoring, logging More ❯
Skills: Working knowledge of advanced predictive modeling, optimization, scenario analysis, and statistical methodologies. Strong grasp of supervised/unsupervised methods, evaluation metrics, feature engineering, and model tuning. Proficiency in Python (pandas, NumPy, Scikit-learn); experience with PyTorch or TensorFlow for deep learning. Experience with API development and connecting AI systems to external platforms. Working knowledge in deep learning techniques, including More ❯
Experience in below: Strong Linux skills with some scripting a plus Strong Network Troubleshooting experience Knowledge of the OSS/BSS/Network Management solutions/Systems. Languages: JAVA, Python, Shell Scripting. Database(s): PostgreSQL, Neo4j, Mysql Knowledge of SNMP, Syslog, ICMP, and SSH is recommended Hands-on experience on RESTful APIs – interconnected software components interaction, engineering and testing (e.g. More ❯
of code management/reviews/branching strategies Desired Experience in Linux OS/Bash. Proficiency in SQL or another relational database language. At least one scripting language (e.g. Python, Perl, Javascript). Proficiency in MS Office Suite: including Word, PowerPoint, and Excel (ability to create formulas and to analyse data). We are dedicated to fostering a collaborative, engaging More ❯
world business problems. End-to-End Data Science: Practical knowledge across the full lifecycle—from feature engineering and model design to validation, deployment, and monitoring. Technical Proficiency: Fluency in Python, SQL, or similar languages, and experience with deep learning frameworks such as TensorFlow, Keras, PyTorch, or MXNet. Agile & DevSecOps: Familiarity with Agile methodologies and DevSecOps practices, including Git for version More ❯
helping grow our collective data engineering capability. What we're looking for Solid experience as a Senior/Lead Data Engineer in complex enterprise environments. Strong coding skills in Python (Scala or functional languages a plus). Expertise with Databricks, Apache Spark, and Snowflake (HDFS/HBase also useful). Experience integrating large, messy datasets into reliable, scalable data products. More ❯
Data Science, Bioinformatics, Engineering, or a related field, or equivalent experience. Proven experience designing and deploying MLOps pipelines (MLflow, Azure ML, Azure DevOps etc). Strong programming skills in Python and familiarity with common ML/AI libraries (scikit-learn, tensorflow, Keras etc.). Experience implementing machine learning and large language models (LLMs), encompassing deployment, monitoring, and retraining. Familiarity with More ❯
modelling—from conceptual to logical and physical—and familiarity with data catalogues, knowledge graphs, or ontology tools. Proven experience managing or mentoring other data engineers. Solid programming skills in Python and SQL, and familiarity with tools such as Git, CI/CD workflows, Docker, and Kubernetes. Experience with data pipeline orchestration tools (e.g., Dagster) and modern data stack components. Why More ❯
data visualisation and storytelling - able to translate technical outputs into commercial insights for senior stakeholders. Technical fluency across: BI tools (e.g., Power BI, Tableau, Qlik) SQL and data engineering Python or R Cloud technologies (AWS, Azure, GCP) Strong communication and stakeholder management skills; comfortable influencing C-suite clients. Advantageous competencies (but not essential): Exposure to AI/ML, NLP or More ❯
client-facing environments Deep experience with incident management, root cause analysis, and production troubleshooting Strong Linux systems knowledge, including filesystems, networking, and system internals Programming skills in GoLang and Python and experience with infrastructure tools or observability stacks (e.g. Grafana, Prometheus, EFK) Confident working with cloud-native platforms and tools - e.g. Kubernetes, Terraform, AWS/GCP, Docker Excellent communicator under More ❯
science, analytics, and operational research techniques at scale to address business challenges. Minimum 4 years' hands-on experience as a Data Scientist, with exposure to productionised models. Proficiency in Python (production-level) and SQL; confident with modern ML/AI libraries such as scikit-learn, TensorFlow, or PyTorch. Familiarity with MLOps frameworks, model deployment, and cloud-based platforms (Databricks, AWS More ❯
line An advocate for the development of analytical approaches and the adoption of new techniques, including data science, machine learning and AI Solid experience with data manipulation Experience with Python, Git (or other versioning tools) and MLOps is preferred An understanding of machine learning and statistical theory Experience with Azure and AWS is desirable Experience of Radar software is desirable More ❯
