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Data Scientist
Build and optimize machine learning models for time-series forecasting and predictive analytics using Python, PySpark, and SQL to drive business value in healthcare logistics.
Consultant, Scrum Master - India
Coach Agile teams at a Fortune 100 insurer, removing blockers and guiding Scrum/Kanban practices to deliver secure software solutions that protect customer data.
Architect, Data Engineering
Design and lead enterprise-scale data platforms, pipelines, and ML solutions for clients, using cloud-native tools and modern architectures like Lakehouse and Data Mesh.
AWS Data Platform Architect, Technology Consulting- London, Leeds, Manchester or Newcastle
Designs and leads AWS-based data and AI platforms for public-sector and regulated clients, integrating ML, GenAI, and streaming pipelines while ensuring security and governance.
Data Platform Architect, Technology Consulting
Design and deliver cloud-native data platforms with AI/ML integration for enterprise clients, focusing on scalable analytics, real-time processing, and governance.
Manager, AI Enablement
By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice…
Senior Data Engineer
Build and maintain scalable data pipelines and orchestration with Airflow and Databricks to power advanced analytics and data science workflows for a major UK retailer.
Senior Machine Learning Engineer, Agentic Science/Generative Models, AI for Biology & Translation (AIBT)
Build and scale AI agents and foundation models for drug discovery, integrating biological data and deploying robust MLOps/AgentOps systems in a biotech R&D environment.
The Hub | AI Engineer | Neurons
Build and deploy AI systems that predict consumer reactions to creative content using neuroscience data, generative AI, and multi-modal models in a production environment.
Data Science and Engineering Manager
Lead a small team that builds and maintains scalable data infrastructure, ML pipelines, and AI-driven features to power AllTrails’ map quality, content, and member experiences.
Senior Machine Learning Engineer
Build and scale MLOps infrastructure for AI systems using Python, Kubernetes, and Kafka, while collaborating with data scientists to deploy LLM and generative AI workflows.
Senior MLOps Engineer
Senior MLOps Engineer builds and maintains scalable AI/ML pipelines for drug-discovery models, bridging research and production in a life-sciences org.
AI Engineer
Design and build AI/ML models to solve real-world problems, using Python and frameworks like PyTorch or TensorFlow, while collaborating in a hybrid office setup.
Amazon AI Solution Architect
Design and deploy AI systems for AWS customers, focusing on GenAI, LLMs, RAG, and agentic workflows using AWS Bedrock, SageMaker, and vector databases.
AI Engineer (Remote)
Build and deploy AI models, RAG pipelines, and LLM-powered systems for early-stage startups backed by a VC firm.
Lead AI & Data Science Principal Consultant
Lead AI and data-science engagements, designing and delivering production-grade AI solutions for enterprise clients while mentoring teams and advising executives.
Machine Learning Software Engineer (Remote)
Build and ship ML infrastructure for autonomous freight systems: multimodal data pipelines, model training/evaluation workflows, and low-latency inference tooling using PyTorch/TensorFlow/JAX.
Principal Data Scientist
Lead enterprise AI engineering at a large utility: design scalable agentic and generative AI systems in Python/AWS Bedrock, set standards, and guide production deployment for safety, reliability, and operational efficiency.
Manager, Data & AI
Job Summary The Manager, Data & AI is responsible for delivering high‑quality analytics, BI solutions, AI/ML initiatives, and data products, while ensuring alignment to enterprise‑wide data strategy, governance,…
Machine Learning Technical Architect
Design and implement enterprise-grade MLOps/LLMOps pipelines on AWS SageMaker and EKS, focusing on model lifecycle management, CI/CD, monitoring, and governance for AI/ML systems.