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Our client, a growing Business Intelligence organization, is hiring a ServiceNow HR Business Process Consultant to join the team in New Jersey on a contract basis. The successful candidate will translate complex operational requirements into scalable, user-focused ServiceNow solutions, while playing a key role in streamlining workflows, driving platform adoption and supporting operational excellence across multiple business functions.
Responsibilities
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Collaborate with business stakeholders to gain a deep understanding of processes, pain points, and opportunities for transformation across multiple teams.
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Design and recommend streamlined, efficient business workflows that leverage ServiceNow capabilities.
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Act as the key liaison between business teams and technical delivery groups to ensure alignment and clarity.
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Lead requirements gathering, process mapping and solution validation to support effective implementation.
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Ensure processes are standardized, compliant and adhere to organizational governance frameworks.
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Drive platform adoption through change management, training and targeted communication initiatives.
Skillset
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Extensive expertise in HR, Audit, Workplace, Procurement or Global Security domains.
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Strong knowledge of end-to-end business processes and workflow optimization.
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Proven background in business consulting, process design or ServiceNow functional roles.
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Exceptional communication, stakeholder management, and facilitation skills, with the ability to influence and collaborate across all levels.
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Skilled at simplifying complex challenges and delivering clear, actionable recommendations.
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Experience with ServiceNow modules, including HRSD, Procurement Operations, GRC/Audit, Workplace Service Delivery, or Security Operations.
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ServiceNow or business process/lean methodology certifications are highly desirable.
Applied LLM Engineer
Location: London, England (Hybrid)
Contract: Fixed term Contract; 4-6 months initially
Rate: Daily Rate (Outside IR35)
Our client, an award-winning advertising company, are hiring an Applied LLM Engineer to join their team on a 4-6 month fixed-term contract in London. The successful candidate will take full ownership of the technical solution, designing and delivering an AI platform that automates advertising creations while incorporating human-in-the-loop feedback to maintain high-quality outputs.
Responsibilities
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Lead the architecture, development and delivery of the company’s platform.
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Design and build LLM-powered workflows for AI-assisted advertising generation.
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Implement human-in-the-loop feedback loops, capturing accept/reject decisions and rationale to continuously improve output.
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Deliver a web-based application with downloadable assets or shareable links.
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Ensure the platform maintains brand compliance and design quality, achieving approximately 95% AI accuracy with designer sign-off.
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Collaborate directly with designers and stakeholders to refine and optimise outputs.
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Take full ownership of all technical decisions and delivery outcomes.
Skillset
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Strong experience in full-stack software engineering.
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Hands-on experience deploying LLMs or Applied AI in production environments.
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Experience with AI-driven content generation, preferably visual or design-focused.
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Ability to design feedback-driven learning systems with human-in-the-loop processes.
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Strong product mindset, able to translate business needs into functional software.
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Comfortable collaborating with end users and non-technical stakeholders.
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Familiarity with Gemini, OpenAI, or similar LLM platforms is a bonus.
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Background in creative, design or media production environments is a plus.
Staff MLOps Engineer
Remote
My client is a HealthTech startup helping individuals get healthier!
Sitting at the intersection of machine learning, infrastructure, and production systems. You'll get to build solutions across ML infra and MLOps that help drive velocity in Machine Learning to ship ML products quickly and safely.
You'll have autonomy and ownership to create, innovate and build solutions for the future of ML at the company creating huge impact.
You'll also get to build feature stores, test new MLOps tools, Optimize GPUs, inference and more.
What else do you get?
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Base Salary: 220-270k
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Equity
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Fully Remote
What do you need to be successful?
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Experience building solutions that drive ML product build velocity for the last 5+ years like ML Platform, ML Infra and MLOps.
- Experienced with areas like real-time inferencing, GPU optimization, Feature store builds and over all ML lifecycle.
- Worked with Cloud tools (GCP preferred or open to learning)
*Please note due to limited resources we are currently only shorlisting those who can work without visa support like Green Crad or Citizenship.
Our client, a fast-growing AI startup, is hiring an AI/ML Engineer to join their team in New York. The successful candidate will focus on building the core Copilot product, with ownership across the full ML lifecycle - from data pipelines and model training to embeddings, retrieval, serving and continuous iteration in production.
Responsibilities
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Design, develop and deploy production-grade Machine Learning systems in Python, moving well beyond experimentation and notebooks.
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Take ownership of key components of the NLP and LLM stack, including embeddings, retrieval pipelines, RAG architectures and targeted fine-tuning.
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Build and iterate on recommendation and ranking models that surface who users should engage with and when.
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Work hands-on with vector databases and similarity search to drive relationship intelligence.
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Implement and maintain ML tooling for training, versioning, monitoring and evaluation.
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Collaborate closely with founders, product and engineering to translate ideas into shipped, measurable product capabilities.
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Integrate ML models into production APIs within a TypeScript / Nest.js–heavy environment.
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Continuously optimise latency, cost and performance, including model routing, caching, distillation and quantisation.
Skillset
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Minimum of 3 years of experience building and deploying production ML systems using Python, PyTorch or TensorFlow and scikit-learn.
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Hands-on NLP and LLM experience, including HuggingFace Transformers, embeddings, sentence-transformers and RAG architectures.
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Experience working with both proprietary models (e.g. OpenAI) and open-source LLMs (e.g. Llama, Mistral).
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Strong foundation in classical machine learning, including classification, ranking, supervised and unsupervised learning, and XGBoost or LightGBM.
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Experience with MLOps and infrastructure, such as experiment tracking, model versioning, Docker/Kubernetes, SageMaker or similar systems.
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Practical experience with vector databases, including Pinecone, Qdrant, Weaviate or comparable platforms.
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Strong software engineering fundamentals, with experience integrating ML models into reliable, production-grade systems.
Benefits
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Salary: Circa $250k.
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Equity.
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Health, dental and vision insurance.
Our client, a growing Financial Services company, are hiring a hands-on Full-Stack Engineer to join their team remotely. The successful candidate will play a pivotal role in shaping the engineering culture while tackling real-world financial challenges, with the opportunity to take ownership of projects from concept through to production.
Responsibilities
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Collaborate with customers and internal stakeholders to identify SMB financial challenges, translate them into technical requirements and drive successful delivery.
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Take ownership of the entire software development lifecycle, including design, development, testing and production deployment, in alignment with the product roadmap.
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Continuously refine engineering processes, tools and systems to scale the codebase, increase efficiency and support team growth.
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Play an active role in shaping and strengthening the engineering culture, encouraging collaboration and high performance.
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Proactively identify opportunities to enhance products and business outcomes, contributing beyond your core responsibilities.
Skillset
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Proficient in TypeScript and React, with experience in Node.js / Express.
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Previous experience working at an early-stage, high-growth startup.
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Hands-on engineer who transforms ideas into practical, impactful solutions.
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Proven experience designing and building complex, user-friendly products.
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Skilled in architecting end-to-end solutions for complete products.
Our client, a global life sciences organization, are hiring an experienced OpenShift Subject Matter Expert to join their team in Dublin, Ireland on a contract basis. The successful candidate will design, build and deploy AI-ready infrastructure on OpenShift, delivering robust and scalable platforms capable of supporting AI/ML workloads.
Responsibilities
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Design and deploy AI-ready OpenShift clusters to support AI/ML workloads at scale.
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Build, operate and maintain AI infrastructure on OpenShift.
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Deploy, manage and run AI/ML workloads across OpenShift environments.
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Perform OpenShift and OpenShift AI administration, including platform operations.
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Enable and manage GPU integration within OpenShift e.g. installation, configuration, scheduling.
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Deploy and manage model servers and oversee the full model lifecycle.
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Implement and support MLOps workflows using OpenShift AI.
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Build and maintain CI/CD pipelines using Tekton and Argo CD.
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Implement observability and monitoring solutions (Prometheus, Grafana, Loki, ELK).
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Troubleshoot and resolve complex infrastructure, platform, and workload issues.
Skillset
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Demonstrated hands-on experience administering and operating Red Hat OpenShift platforms.
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Strong Linux systems administration expertise.
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Proficiency in programming and scripting, including Python, Shell and Go.
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Solid knowledge of container technologies and end-to-end container lifecycle management.
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Deep understanding of on-premises infrastructure, including DNS, load balancers, firewalls, enterprise networking and storage platforms.
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Strong knowledge of AI hardware environments, including GPU architecture, scheduling and enablement, as well as server hardware and enterprise storage systems.
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Experience designing and implementing secure platform configurations, including certificate management.
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Excellent troubleshooting, diagnostic and problem-solving skills.
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Exposure to AI/ML models, training techniques, and model types is a plus.
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Experience working across AWS, Azure and on-prem hybrid environments is highly desirable.