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About the Role

We are seeking a hands-on Datacenter Installation Specialist to support data center infrastructure deployments and ISP-related projects. This position focuses on rack and stack activities, fiber infrastructure installation, structured cabling, hardware deployment, and ongoing support within a data center environment.

This is an excellent opportunity for technicians with strong experience in data centers, fiber optics, structured cabling, and network infrastructure installations.

Key Responsibilities

Install and rack servers, switches, storage devices, and network equipment.Perform rack and stack activities including rails, cabinets, PDUs, and cable management systems.Route, terminate, label, and document fiber and copper cabling.Install and maintain fiber infrastructure, patch panels, and ODFs.Perform fiber testing, troubleshooting, and connectivity validation.Support hardware upgrades, replacements, decommissions, and break-fix activities.Read and interpret rack elevations, floor plans, and deployment documentation.Maintain accurate installation records and asset documentation.Support data center expansion and infrastructure upgrade projects.Work closely with engineering, project management, and operations teams.

Required Skills

3+ years of experience in data center installations, rack and stack, or network infrastructure deployments.Hands-on experience installing servers, switches, routers, cabinets, and rack equipment.Experience with fiber optic cabling, termination, patching, and testing.Knowledge of structured cabling standards and best practices.Experience reading rack elevations, schematics, and deployment plans.Strong troubleshooting and hardware break-fix skills.Ability to work onsite and perform physical installation activities.

Preferred Skills

OTDR testing and fiber certification experience.Fusion splicing or fiber troubleshooting experience.Experience supporting ISP, colocation, or hyperscale data centers.Experience with Liquid Cooled Rack (LCR) environments or CDU systems.Remote hands support experience.Strong documentation and customer-facing communication skills.

GCS is acting as an Employment Business in relation to this vacancy.

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Role Summary
This role focuses on building and deploying machine learning solutions that improve personalization, recommendations, and customer experiences across entertainment and digital platforms. The engineer will work with large-scale customer data, develop ML models, create data pipelines, collaborate with data scientists and software engineers, and use experimentation (A/B testing) to improve model performance and user engagement.

Key Skills Required

Python programmingMachine Learning fundamentals (classification, regression, feature engineering, model evaluation)Scikit-learn, TensorFlow, or PyTorchSQL and large-scale data processingGit and software development best practicesData analysis and experimentation

Preferred Skills

Recommendation systems and personalizationRanking algorithmsSpark/PySpark, Databricks, MLflowDocker and AWSA/B testing and model optimization

Ideal CandidateAn early-career ML Engineer (1 to 3 years of experience) who can transform machine learning research into production-ready solutions, work with large datasets, and help drive user engagement through data-driven recommendations.

GCS is acting as an Employment Business in relation to this vacancy.

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Position Summary

We are seeking a Machine Learning Engineer to join a high-performing AI and Data Science team responsible for developing, deploying, and maintaining predictive machine learning solutions. This role will focus on designing end-to-end ML pipelines, building scalable predictive models, and operationalizing machine learning workloads in a cloud-based environment.

The ideal candidate will possess strong expertise in Python, PySpark, machine learning frameworks, data analysis, and MLOps practices. Experience working with Large Language Models (LLMs) and deploying machine learning solutions in AWS environments is highly desired.

Key Responsibilities

Design, develop, and deploy machine learning models focused on predictive analytics and business intelligence use cases.Build scalable data processing and feature engineering pipelines using PySpark and distributed computing technologies.Develop, test, and optimize machine learning algorithms using Python and Scikit-learn.Implement and maintain end-to-end MLOps pipelines for model training, deployment, monitoring, and lifecycle management.Work with large structured and unstructured datasets to derive actionable insights and improve model performance.Collaborate with data scientists, software engineers, and business stakeholders to translate requirements into production-ready ML solutions.Support the integration of machine learning models into enterprise applications and workflows.Leverage AWS cloud services to build scalable and reliable machine learning infrastructure.Explore and implement Large Language Model (LLM) solutions where applicable.Participate in model evaluation, performance tuning, and continuous improvement initiatives.

Required Qualifications

5+ years of experience in Machine Learning Engineering, AI Engineering, or related disciplines.Strong programming expertise in Python.Hands-on experience with PySpark and large-scale data processing.Experience developing machine learning models using Scikit-learn.Strong background in data analysis, feature engineering, and statistical modeling.Experience building and maintaining MLOps pipelines and model deployment workflows.Knowledge of machine learning lifecycle management, CI/CD, and production model monitoring.Experience working within AWS cloud environments.Familiarity with Large Language Models (LLMs), NLP, or Generative AI technologies.Strong problem-solving and communication skills.

Technical Environment

PythonPySparkScikit-learnAWSMLOpsLarge Language Models (LLMs)Machine Learning PipelinesPredictive AnalyticsNeural Networks (Preferred)PyTorch / TensorFlow (Preferred)

GCS is acting as an Employment Business in relation to this vacancy.

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Machine Learning Engineer

Position Overview

We are looking for a Machine Learning Engineer I with strong Python programming skills to develop, deploy, and optimize machine learning solutions for ad monetization and personalization. You'll collaborate with cross-functional teams to build scalable ML pipelines, enhance recommendation and targeting models, and deliver production-ready AI solutions that improve user engagement and business outcomes.

Key Responsibilities

Develop, train, and deploy machine learning models for personalization, recommendation, and customer experience applications.Build and maintain scalable data pipelines for feature engineering, model training, validation, and inference.Collaborate with machine learning scientists, data engineers, and software engineers to transition research models into production.Enhance recommendation and ranking models using customer behavioural and transactional data.Monitor, evaluate, and improve model performance through experimentation, A/B testing, and data-driven analysis.Write clean, efficient, and maintainable Python code following software engineering best practices.Optimize machine learning workflows to improve customer engagement and support business objectives.Participate in model deployment, monitoring, troubleshooting, and continuous improvement initiatives.Document machine learning processes, model performance, and technical solutions to support collaboration and knowledge sharing.

Required Qualifications

Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, or a related field.1-3 years of experience in machine learning, including internships, research, or professional experience.Strong programming skills in Python.Solid understanding of machine learning concepts, including supervised learning, feature engineering, model evaluation, classification, and regression.Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.Experience working with SQL and large datasets.Familiarity with Git and software development best practices.

What You'll Learn

Build and deploy production-ready machine learning models at scale.Gain hands-on experience with recommendation systems, personalization, and ranking algorithms.Learn best practices for feature engineering, model monitoring, and performance optimization.Work with large-scale data processing and modern machine learning pipelines.Develop expertise in experimentation frameworks, A/B testing, and data-driven decision-making.Collaborate with experienced machine learning engineers, software engineers, and data scientists on real-world AI solutions.Strengthen your understanding of MLOps concepts, including model deployment, versioning, and lifecycle management.Improve your software engineering skills by contributing to scalable, maintainable, and production-quality codebases.

GCS is acting as an Employment Business in relation to this vacancy.

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The Global Campaign Project Manager is a dedicated project management role responsible for planning, coordinating, tracking, and governing marketing initiatives across the SMB Marketing organization. This position does not own campaign strategy, audience planning, activation, channel execution, campaign performance, or optimization. Instead, the role serves as the operational backbone of the organization by ensuring projects are properly planned, resourced, tracked, and delivered according to agreed timelines and priorities. The Global Campaign Project Manager works closely with Campaign Activation, Marketing Automation, Lifecycle Marketing, Insights, Data Operations, Solution Architecture, Commerce, Enablement, Technical SEO, Digital Experience, agency partners, and the Corporate Affairs Project Management team to ensure alignment across all workstreams. This role is also responsible for work management governance within Wrike, ensuring all work is visible, prioritized, tracked, and reported consistently across the organization.

Key Responsibilities:

Project Planning & Coordination

Develop project plans for approved marketing initiatives and campaignsCreate and maintain project schedules, timelines, milestones, and dependenciesCoordinate activities across multiple teams to ensure work progresses according to planFacilitate project kickoffs, planning meetings, status meetings, and stakeholder reviewsMonitor project progress and communicate updates to stakeholders and leadershipEnsure project documentation remains accurate and current throughout the project lifecycle

Dependency Management

Identify and manage dependencies across teams, systems, vendors, and stakeholdersCoordinate handoffs between functional teamsProactively identify bottlenecks and risks that could impact project timelinesEscalate issues and facilitate resolution when projects encounter obstaclesSupport leadership in making informed prioritization and resource decisions

Project Governance & Reporting

Maintain project status reports, dashboards, RAID logs, and executive updatesEnsure projects follow established governance processes and approval workflowsMonitor project health and provide visibility into schedule performance, risks, and resource impactsSupport leadership reporting and portfolio reviewsEstablish consistency in project management standards, templates, and operating procedures

Work Management Governance (Wrike)

Serve as the primary owner of project visibility and governance within WrikeEnsure all projects, initiatives, enhancements, operational activities, and campaign-related work are logged and maintained within WrikeDrive adoption and compliance with established work management processesEnsure project plans, timelines, statuses, and assignments remain accurate and currentMaintain portfolio-level visibility into active work across SMB MarketingSupport reporting and dashboard development to improve transparency and decision-making

Resource Management & Capacity Planning

Monitor team capacity, workload distribution, and resource utilization across SMB MarketingPartner with team leaders to identify resource constraints and workload imbalancesEnsure time tracking is completed accurately and consistentlyAnalyze utilization and workload data to support planning and forecasting activitiesProvide leadership with visibility into team capacity, project demand, resource allocation, and delivery risksRecommend adjustments to priorities, timelines, and resource assignments when capacity challenges arise

Operational Excellence

Support continuous improvement of project management processes and workflowsIdentify opportunities to improve efficiency, transparency, and collaboration across teamsPromote disciplined project management practices and accountabilityDrive standardization of project intake, prioritization, planning, and reporting processesPartner with Corporate Affairs Project Management teams to align best practices where appropriate

Role Distinction

Global Campaign Project Manager Owns project planning, timeline management, dependency management, resource coordination, capacity planning, work management governance, Wrike compliance, project reporting, risk management, stakeholder communication, process adherence, and operational transparency.

Campaign Activation Manager Owns campaign activation planning, audience readiness, segmentation requirements, channel coordination, marketing execution readiness, campaign launch requirements, measurement requirements, campaign performance monitoring, and optimization recommendations.

GCS is acting as an Employment Business in relation to this vacancy.

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GCS is acting as an Employment Business in relation to this vacancy.

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We're looking for DOCSIS Engineer and you'll review the platform's RF-plant analysis and confirm it reflects what is genuinely happening on a live DOCSIS network. You'll be the human authority that tells the client "yes, this is right" or "here's where it's off, and here's what it's missing."

What you'll be doing

Reviewing automated RF-plant analysis and validating it against what is actually happening on the network - confirming the platform isn't misreading or over-stating the data.Sanity-checking the interpretation of RF performance, signal behavior, and physical-layer impairments across the plant.Assessing the platform's predictive trending - whether its "this is starting to degrade" calls hold up against real-world DOCSIS RF expertise.Delivering a clear, expert read on what's solid, what's inaccurate, and what additional signals should be considered.

What we're looking for

Deep, hands-on DOCSIS RF / HFC physical-layer expertise- gained at a cable operator (MSO) or equipment vendor.Strong ability to read RF plant performance- spectrum behavior, signal levels, noise and impairments - not just protocol or IP-layer data.Practical live-plant diagnostic experience- sweep/balance, signal forensics, and proactive network maintenance (PNM)-style analysis.Solid DOCSIS 3.1 and 3.0 knowledge.Comfort reviewing and critiquing analytic output- forming and clearly communicating an expert verdict.

GCS is acting as an Employment Business in relation to this vacancy.

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