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Design and build AI/ML systems for a global investment firm, integrating generative and traditional models into trading platforms using Python, TensorFlow/PyTorch, and cloud infrastructure.
Data Scientist building production NLP/LLM solutions (RAG, semantic search, NER, summarization) on Databricks with Python for a SaaS platform serving energy and utility infrastructure sectors.
Why this role exists K0rdent AI is the orchestration layer that turns raw, disaggregated GPU infrastructure into a multi-tenant, production-ready AI cloud — without locking companies into a single hyperscaler or…
The Principal Scientist will lead AI/ML and computational projects across early-stage ventures, overseeing method development, platform design, and LLM-based agentic workflows. The role involves managing cross-functional teams and driving technical strategy to accelerate scientific discovery in human health and sustainability.
This role involves leading scientific and machine learning development for hydrology-aware climate modeling within an environmental platform. The scientist will work with large-scale climate datasets and Python-based ML frameworks to build reproducible, physically-informed prediction systems.
Research and build AI-powered tools that improve psychological wellbeing using large language models, reinforcement learning, and computational methods in a fast-moving startup environment.
Lead AI/ML and computational projects to accelerate pharmaceutical R&D, designing agentic workflows that integrate LLMs with omics, biomolecule design, and systems biology tools for end-to-end scientific pipelines.
Develops AI-driven molecular models to advance drug discovery by linking quantum chemistry, reactivity data, and generative design for covalent drug targets, collaborating with chemistry and biology teams.
Encord is looking for a Senior Backend Engineer to join their Foundations team, focusing on building and scaling the distributed systems and data infrastructure that power their AI platform. The role involves end-to-end ownership of backend services using technologies like Python, Kubernetes, and GCP.
Build and maintain scalable full-stack systems for the UK’s largest automotive marketplace using Java/Spring Boot, React/Angular, and Kafka, while mentoring junior engineers.
Developing and deploying production ML/DL models for time series forecasting and financial market prediction in a DeFi and algorithmic trading product team, using Python, PyTorch, and gradient boosting frameworks.
The Machine Learning Engineer will design, develop, and deploy scalable ML models for Capital Markets applications using Python, PySpark, and various ML frameworks. The role involves managing the full ML lifecycle, including pipeline development, model optimization, and production integration.
The Lead ML/AI Platform Engineer will own the end-to-end machine learning infrastructure, including training, model serving, and integration with Java microservices. The role focuses on driving the company's GenAI and agentic workflow strategy using AWS-based tools and open-source ML frameworks.
Design, deploy, and maintain cloud and on-prem infrastructure for aerospace and defense systems, ensuring reliability and security for remotely piloted aircraft and surveillance platforms.
Staff Applied AI/ML Scientist at lululemon designing and deploying machine learning and predictive/generative AI models (demand forecasting, personalization, search, automation, multimodal content) at enterprise scale using Python and PyTorch.
Build multimodal embeddings and LLM-based representations for Reddit Ads, using NLP/CV models to power relevance, targeting, and ranking systems.
Data Science & AI Consultant Location: Bristol, London, or Manchester (Hybrid working) Security Clearance: Active DV clearance is essential Salary: £45,000-70,000 DOE As a Data Science & AI Consultant, you will…
Build and deploy machine learning models for startups and life-science companies using Python, PyTorch, and TensorFlow in a fully remote, globally distributed team.
Deploy Fundamental's NEXUS Large Tabular Model into production for Houston-based Oil & Gas enterprise customers, performing end-to-end ML work including benchmarking against XGBoost/LightGBM, data engineering, feature engineering, and last-mile integration (VPC, on-prem, air-gapped).
Develops backend systems for AI-driven 3D design review, focusing on geometry parsing, model analysis, and AI-assisted workflows to improve engineering quality and reduce rework cycles.
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