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Lead the MLOps and ML infrastructure for a global recommender system, owning deployment, scalability, and production monitoring using AWS SageMaker, Python, and MLflow.
Senior AI & Data Scientist builds, deploys, and evaluates ML models end-to-end, from forecasting to LLM fine-tuning, while mentoring junior team members and translating technical results for clients.
Senior AI & Data Scientist who designs, builds, and deploys end-to-end ML models (forecasting, classification, LLM fine-tuning) for enterprise clients, bridging business needs with technical execution.
About the job Artefact is a next-generation data and AI consulting firm dedicated to accelerating the adoption of data and AI to create measurable business impact across the full enterprise value chain.We sit at the…
Lead Software Engineer building AI-native enterprise applications for IFS's Enterprise Asset Management team, using Go, TypeScript, DDD, and event-driven architecture to integrate LLM capabilities into production software.
AppRecode is an AI-powered DevOps and cloud engineering company working with fintech, telecom, and healthcare teams across Europe and the US. We build, secure, and run the infrastructure behind production systems —…
DVT is a leading technology consulting and software engineering company delivering innovative solutions across Africa and internationally. We partner with clients to solve complex business challenges through software…
Maintains and optimizes GPU/Kubernetes infrastructure for AI workloads, deploys and secures LLM serving stacks, and builds MLOps pipelines for training and inference.
Intern designs and deploys MLOps platforms, automates observability and resource management, and ensures reliability for ML training and inference systems.
As an ML Platform Engineer, youll help build and evolve the infrastructure that enables machine learning teams to develop, deploy, and operate models efficiently at scale. Youll work closely with Data Scientists, Data…
The Technical Product Owner at TD's Layer 6 AI research centre leads the delivery of production-grade AI/ML solutions by coordinating cross-functional teams of scientists and engineers. The role involves translating business goals into technical roadmaps, managing architecture trade-offs, and overseeing MLOps and governance.
The AI Engineer will develop LLM-powered agents and RAG pipelines to automate workflows and build conversational interfaces for PureFacts' financial SaaS platform. The role focuses on integrating AI models, ensuring system reliability, and collaborating with cross-functional teams to deliver production-ready AI copilots.
This role involves performing adversarial testing and red teaming on foundation models and AI systems to identify and remediate security vulnerabilities. The engineer will design and train ML models and SLMs while collaborating with client teams to ensure robust security across model, application, and data pipelines.
The Senior Data Scientist will lead machine learning efforts for physical measurement data, focusing on anomaly detection and classification using Python. The role involves improving existing production models, mentoring team members, and collaborating with hardware specialists to enhance data quality and model performance.
The AI Engineer will design, develop, and deploy scalable agentic AI systems and generative AI applications using the Databricks platform. This role involves collaborating with data scientists and engineers to integrate AI models into production environments while utilizing Python, SQL, and modern cloud architectures.
Principal Engineer defines the technical vision for Acceldata’s Open Data Platform, leading architecture and open-source contributions for scalable, distributed data systems powering enterprise analytics and AI.
Lead a team of ML/AI engineers, owning the ML/AI product vision and translating local models into enterprise-grade products on PureFacts' SaaS platform using Python, ML frameworks, MLOps, and Azure cloud infrastructure.
Build secure, scalable AWS serverless services that power AI/LLM-driven capabilities across Diligent's GRC SaaS platform, using TypeScript/Python with an AI-augmented engineering culture.
An AI/ML internship focused on developing multi-agent systems, agentic coding tools, and ML models for trading infrastructure. Core work involves building agent orchestration, deploying ML models, and optimizing MLOps pipelines in a fintech environment.
Builds and deploys AI/ML pipelines and data infrastructure for DHL’s global logistics operations, using cloud (Azure/GCP) and on-prem tools like Spark, Kafka, and Kubeflow to process petabytes of transactional data into predictive models and analytics.
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