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Top Machine Learning Jobs in Edinburgh
As a Senior Machine Learning Engineer at Smartcat, you will enhance the computer vision capabilities of our Language AI platform. You'll manage data labeling, optimize ML training pipelines, and oversee model deployment and performance monitoring while driving innovation in Image and Video Translation products.
The GCOA Enterprise Architect at Lilly is responsible for developing innovative technology solutions that enhance business productivity and efficiency. This role involves strategizing technology roadmaps, determining system architecture, aligning IT with business goals, and documenting processes through architectural models. The architect will work closely with stakeholders to ensure optimal technology usage and integrate emerging technologies into business processes.
As a Senior Solution Consultant, you'll drive the design, demonstration, and presentation of Five9's AI Solutions, focusing on customer engagement and contact center operations. Responsibilities include collaborating with sales teams, providing pre-sales support, mentoring junior consultants, and delivering customized demonstrations to exceed customer expectations.
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The Lead Data Strategist will work closely with clients to drive Data & AI transformation, focusing on the Lakehouse architecture. Responsibilities include supporting sales opportunities, providing thought leadership, and ensuring customer success by advocating for Databricks solutions. This role requires collaboration with regional leaders and continuous engagement with industry trends to elevate strategic offerings at the CXO level.
As a Staff Machine Learning Engineer at Mozilla, you will lead the development of Generative AI solutions for Firefox. Your responsibilities include designing and integrating these solutions, building infrastructure for model training and inference, and ensuring the reliability of models through robust validation. You'll also collaborate with multiple teams to enhance AI-driven experiences for users.
The Senior ML Engineer will design and engineer innovative projects in Natural Language Processing, focusing on building and optimizing LLM-based solutions and ML/DL systems. Responsibilities include developing pipelines for data and inference, transforming datasets, and ensuring efficient architectures for production deliverables.
The AI Productivity Engineer role involves supporting the development and implementation of collaboration and conversational AI platforms within the company. The position is aimed at recent graduates, offering opportunities to learn about AI and software engineering, collaborate with IT teams, contribute to system integration, and improve employee experiences through AI-driven solutions.
As a Software Engineer on the ML Frameworks team, you will develop and optimize compilers for semiconductor products, benchmark and enhance machine learning applications, and collaborate with engineers to address hardware and software needs.
As a Senior AI/ML Engineer, you will design, implement, and maintain machine learning algorithms and systems, collaborate with cross-functional teams, and integrate AI models into existing applications. You will advocate for best practices within the team while working in regulated environments, and ensure smooth operations by developing RESTful APIs and CI/CD pipelines.
As a Senior ML Engineer, you will lead projects concerning communication activities and machine learning for core business tasks. You will be responsible for developing ML models, collaborating with cross-functional teams, and sharing knowledge within your team. Your role involves ensuring projects progress from data to production while leveraging various ML tools and technologies.
As a ML Engineer, you will create and implement features to enhance revenue management for lodging customers. You'll develop machine learning models, analyze data to identify trends, and collaborate with various teams to optimize product features and pricing strategies.
As a ML Engineer at Cloudbeds, you will develop and implement features for revenue management by utilizing machine learning models and data analysis to optimize pricing strategies. You will work with cross-functional teams to enhance product functionality, build data pipelines, and analyze trends to drive revenue growth for customers in the hospitality sector.
As a ML Engineer, you will develop and implement features that optimize pricing strategies for lodging customers. Your work will involve creating machine learning models, data analysis, and collaborating with cross-functional teams to improve product functionality and drive revenue growth.
As a ML Engineer at Cloudbeds, you will build and implement features to optimize revenue for lodging customers. This role involves developing machine learning models, maintaining data pipelines, analyzing data trends, and collaborating with cross-functional teams to drive product improvements.
As a ML Engineer, you will develop features for a revenue management application, utilizing machine learning and heuristic data. You'll collaborate with teams to enhance product performance, analyze data trends, and communicate insights. Your role includes building data pipelines and implementing machine learning models in a cloud environment.
As a Machine Learning Engineer, you will develop and implement features that optimize revenue for lodging customers. This includes building machine learning models, collaborating with teams for product improvements, managing data pipelines, and conducting data analysis to inform strategies.
As a ML Engineer, you will build end-to-end features for revenue optimization for lodging customers, develop and implement machine learning models, collaborate with cross-functional teams, maintain data pipelines, analyze data sets, and communicate findings to stakeholders.
As a Machine Learning Engineer at Cloudbeds, you will build end-to-end features that assist lodging customers in optimizing their pricing strategies. You'll collaborate with cross-functional teams, apply machine learning models, analyze data, and improve product functionalities to drive revenue growth.
As a Machine Learning Engineer, you will develop end-to-end features for optimal pricing strategies in the hospitality sector. You will implement machine learning models, collaborate with cross-functional teams, maintain data pipelines, and analyze data trends to improve product performance and revenue for lodging customers.
As an ML Engineer, you will implement features to optimize hotel pricing strategies using machine learning and heuristic data. Responsibilities include developing ML models, collaborating with product teams, building data pipelines, analyzing data for trends, and communicating insights across teams.
The Engineering Manager will lead a cross-functional team responsible for core translation systems, drive the technical roadmap aligned with business goals, mentor team members, establish software development best practices, and provide technical leadership in AI/ML development to enhance product offerings.
As a Senior ML Platform Engineer, you will enhance the ML infrastructure for the R&D department, ensuring researchers can efficiently train models at scale while managing cloud infrastructure and providing a seamless user experience. Your role will involve working with GPU clusters and collaborating closely with research teams.
The Senior AI Ops and ML Engineer will enhance GSK's network infrastructure through AI-driven solutions for anomaly detection, predictive analytics, and automated remediation. Responsibilities include automating network tasks, developing CI/CD pipelines, collaborating on observability tools, conducting root cause analysis, and mentoring junior engineers.
As a Software (ML Product) Engineer, you will enhance the user experience of ML tools by optimizing workflows and processes. You will collaborate with technical product managers, contribute to defining efficient ML practices, and improve DVC, an open-source tool for machine learning. A strong background in deep learning and system design is necessary to transform current workflows and engage with the ML community.
As a Senior/Lead ML Engineer, you will own components of the Machine Learning pipeline, working with various data types, developing and deploying models, and documenting processes. You'll shape the technical direction and help mentor other engineers while participating in project management.
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