66 Sentiment Analysis jobs in the United Kingdom

Job Description:

We are seeking an experienced Machine Learning Engineer with expertise in big programmes and has contributed to the delivery of complex business cloud solutions. The ideal candidate will have a strong background in Machine Learning engineering and an expert in operationalising models in the Databricks MLFlow environment (chosen MLOps Platform).

Responsibilities:

• Collaborate with Data Scientists and operationalize the model with auditing enabled, ensure the run can be reproduced if needed.
li>Implement Databricks best practices in building and maintaining economic modelling (Machine Learning) pipelines.
• Ensure the models are modular. Ensure the model is source-controlled with agreed release numbering.
• Extract any hard-coded elements and parameterise them so that the model execution can be controlled through input parameters.
• Ensure the model input parameters are version-controlled and logged to the model execution runs for auditability.
• Ensure model metrics are logged to the model runs.
• Ensure model logging, monitoring, and alerting to make sure any failure points are captured, monitored and alerted for support team to investigate or re-run of the model involves running of multiple experiments and choosing the best model (champion challenger) based on the accuracy/error rate of each experiment, ensure this is done in an automated manner.
li>Ensure the model is triggered to run as per the defined schedule. If the process involves executing multiple models feeding each other to produce the final business outcome, orchestrate them to run based on the defined dependencies.
• Define and Maintain the ML Frameworks (Python, R & MATLAB templates) with any common reusable code that might emerge as part of model developments/operationalisation for future
• models to benefit.
• Where applicable, capture data drift, concept drift, model performance degradation signals and ensure model retrain.
• Implement CI/CD pipelines for ML models and automate the deployment.
• Maintain relevant documentation.

Requirements:

• Bachelor's degree in a relevant field.
• Minimum of 5 years of experience as a business analyst, with a focus on capturing and documenting business requirements and business processes.
• Strong understanding of banking and financial industry practices and regulations.
• Solid knowledge of Data Management process, data analysis and modelling techniques.
• Experience in monetary policy analysis (nice to have)
• Experience in time series database analysis
• Familiarity with business intelligence tools and concepts.
• Strong analytical and problem-solving skills.
• Experience in managing software development lifecycles within Agile frameworks to ensure timely and high-quality delivery.
• Excellent communication and collaboration skills.
• Ability to adapt to changing requirements and priorities in a fast-paced environment.

Spearheading the integration of machine learning into cutting-edge electronics

This innovative team of engineers and scientists are using machine learning tightly integrated with modern electronics to create new classes of products and radically alter the shape, performance and effectiveness of existing ones. As industry goes through a machine learning revolution you can be here, leading the charge.

You will work across the whole machine learning development lifecycle from initial concepts through data collection, cleaning and preparation to prototyping, testing and evaluation. With your models integrated with leading edge electronics, the final products are fully functional prototypes and demonstrator units manufactured at small scale. What’s special about this group is they do this dozens of times per year working across multiple domains. You can be working on computer vision for one project and generative models for the next. 

Requirements:

• Strong knowledge of Python and its use in machine learning including hands-on experience building products with modern ML frameworks such as TensorFlow and PyTorch
li>Broad knowledge of machine learning techniques across multiple domains and the ability to transition into new domains quickly
• A top degree in a STEM subject
• UK national

While not required, experience deploying machine learning onto a range of hardware from resource constrained embedded systems through to edge computing is desirable. As is any knowledge of GPU programming languages and frameworks (CUDA, ROCm, etc).

Your future colleagues will be similarly highly skilled, with experience across industry and the drive to innovate. You will find yourself in a low-management work environment that encourages teamwork and respect for individuals’ expertise. Benefits include private medical insurance, generous pension scheme and access to local social and sports clubs. Please note, you are required to be onsite full-time for this position.

Another top job from ECM, the high-tech recruitment experts.    

Even if this job's not quite right, do contact us now - we may well have the ideal job for you. To discuss your requirements call (phone number removed) or email your CV. We will always ask before forwarding your CV.

Please apply (quoting ref: CV27413 ) only if you are eligible to live and work in the UK. By submitting your details you certify that the information you provide is accurate.

Role: Machine Learning Operations Engineer
Location: Oxfordshire
Salary: 65,000 - 75,000

This is an exciting opportunity to join a world leading company specialising in motion capture and tracking systems, with products used globally in the entertainment, engineering, and life sciences sectors. My Client are looking for a talented Machine Learning Operations Engineer to support and enhance their cutting edge machine learning capabilities.

The Role

You will join a collaborative Research and Development team based in Oxford, contributing to the development and maintenance of a modern ML operations stack. This includes data acquisition pipelines, data management, and machine learning model training infrastructure. The environment includes both self-managed on premise systems and cloud-based infrastructure, primarily using AWS.

You will have the opportunity to influence the technical direction of the ML Ops team, propose new areas for development, and potentially lead your own projects.

This is a hybrid role combining remote and on site working. There is no expectation to be available outside core business hours.

Key Responsibilities

• Maintain and improve ML Ops infrastructure
• Manage on premise Kubernetes clusters and ML pipelines
• Integrate ML toolkits into operational workflows
• Collaborate with ML developers to streamline workflows
• Suggest and implement technical improvements and new tools

Required Skills and Experience

• Academic background (research Masters level) or industry experience in a relevant field
• Strong experience managing on premise Kubernetes clusters
• Deep knowledge of Kubeflow or similar systems such as MLflow
• Proficient in Python and experienced with Linux systems
• Familiar with AWS services such as Cognito, S3, EC2 and Lambda
• Experience working with ML frameworks such as PyTorch or Lightning
• Capable of designing and delivering ML Ops solutions across various platforms

Desirable Skills

• Background in DevOps with experience in CI systems such as Jenkins
• Familiarity with infrastructure as code tools such as Ansible
• Interest in human motion capture, sports tech, or animation
• Exposure to C++ is a bonus

Benefits

• 65,000 - 75,000 (DOE)
• 10 percent company pension
• 25 days annual leave plus bank holidays
• Life assurance
• Private medical insurance including dental and optical
• Permanent health insurance
• Cycle to work scheme
• Free on site parking

WR Engineering are the #1 recruitment partner for engineering, manufacturing & technical sales jobs. We recruit for permanent and contract jobs UK wide.

WR is acting as an Employment Agency in relation to this vacancy.

Job Description:

We are seeking an experienced Machine Learning Engineer with expertise in big programmes and has contributed to the delivery of complex business cloud solutions. The ideal candidate will have a strong background in Machine Learning engineering and an expert in operationalising models in the Databricks MLFlow environment (chosen MLOps Platform).

Responsibilities:

• Collaborate with Data Scientists and operationalize the model with auditing enabled, ensure the run can be reproduced if needed.
li>Implement Databricks best practices in building and maintaining economic modelling (Machine Learning) pipelines.
• Ensure the models are modular. Ensure the model is source-controlled with agreed release numbering.
• Extract any hard-coded elements and parameterise them so that the model execution can be controlled through input parameters.
• Ensure the model input parameters are version-controlled and logged to the model execution runs for auditability.
• Ensure model metrics are logged to the model runs.
• Ensure model logging, monitoring, and alerting to make sure any failure points are captured, monitored and alerted for support team to investigate or re-run of the model involves running of multiple experiments and choosing the best model (champion challenger) based on the accuracy/error rate of each experiment, ensure this is done in an automated manner.
li>Ensure the model is triggered to run as per the defined schedule. If the process involves executing multiple models feeding each other to produce the final business outcome, orchestrate them to run based on the defined dependencies.
• Define and Maintain the ML Frameworks (Python, R & MATLAB templates) with any common reusable code that might emerge as part of model developments/operationalisation for future
• models to benefit.
• Where applicable, capture data drift, concept drift, model performance degradation signals and ensure model retrain.
• Implement CI/CD pipelines for ML models and automate the deployment.
• Maintain relevant documentation.

Requirements:

• Bachelor's degree in a relevant field.
• Minimum of 5 years of experience as a business analyst, with a focus on capturing and documenting business requirements and business processes.
• Strong understanding of banking and financial industry practices and regulations.
• Solid knowledge of Data Management process, data analysis and modelling techniques.
• Experience in monetary policy analysis (nice to have)
• Experience in time series database analysis
• Familiarity with business intelligence tools and concepts.
• Strong analytical and problem-solving skills.
• Experience in managing software development lifecycles within Agile frameworks to ensure timely and high-quality delivery.
• Excellent communication and collaboration skills.
• Ability to adapt to changing requirements and priorities in a fast-paced environment.

Spearheading the integration of machine learning into cutting-edge electronics

This innovative team of engineers and scientists are using machine learning tightly integrated with modern electronics to create new classes of products and radically alter the shape, performance and effectiveness of existing ones. As industry goes through a machine learning revolution you can be here, leading the charge.

You will work across the whole machine learning development lifecycle from initial concepts through data collection, cleaning and preparation to prototyping, testing and evaluation. With your models integrated with leading edge electronics, the final products are fully functional prototypes and demonstrator units manufactured at small scale. What’s special about this group is they do this dozens of times per year working across multiple domains. You can be working on computer vision for one project and generative models for the next. 

Requirements:

• Strong knowledge of Python and its use in machine learning including hands-on experience building products with modern ML frameworks such as TensorFlow and PyTorch
li>Broad knowledge of machine learning techniques across multiple domains and the ability to transition into new domains quickly
• A top degree in a STEM subject
• UK national

While not required, experience deploying machine learning onto a range of hardware from resource constrained embedded systems through to edge computing is desirable. As is any knowledge of GPU programming languages and frameworks (CUDA, ROCm, etc).

Your future colleagues will be similarly highly skilled, with experience across industry and the drive to innovate. You will find yourself in a low-management work environment that encourages teamwork and respect for individuals’ expertise. Benefits include private medical insurance, generous pension scheme and access to local social and sports clubs. Please note, you are required to be onsite full-time for this position.

Another top job from ECM, the high-tech recruitment experts.    

Even if this job's not quite right, do contact us now - we may well have the ideal job for you. To discuss your requirements call (phone number removed) or email your CV. We will always ask before forwarding your CV.

Please apply (quoting ref: CV27413 ) only if you are eligible to live and work in the UK. By submitting your details you certify that the information you provide is accurate.

Machine Learning Engineer Remote (UK Only | No Visa Sponsorship)
Work on AI Products for US Tech Companies

Talent Hero helps UK-based professionals land remote roles with innovative US businesses. We're hiring Machine Learning Engineers to build and deploy production-grade ML systems that solve real-world problems at scale.

If you're experienced with model design, training, and deployment and want .

WHJS1_UKTJ

Machine Learning Engineer Remote (UK Only | No Visa Sponsorship)
Work on AI Products for US Tech Companies

Talent Hero helps UK-based professionals land remote roles with innovative US businesses. We're hiring Machine Learning Engineers to build and deploy production-grade ML systems that solve real-world problems at scale.

If you're experienced with model design, training, and deployment and want .

WHJS1_UKTJ

At Permutable AI, were building intelligent systems to automate market analysis using advanced NLP and multi-LLM frameworks. Our goal is to dramatically accelerate how financial information is processed, understood, and acted on, enabling faster, smarter decisions for financial analysts. As a small, ambitious start-up, youll work directly with our founder and a core team of talented.

WHJS1_UKTJ