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Build and deploy ML systems on Instacart's Economics team, blending economic theory with machine learning to solve marketplace problems like matching, logistics, online advertising, and causal inference using Python, SQL, Pandas, scikit-learn, and XGBoost.
Develop open-source ML tools and a flagship product, packaging models into reusable software components and building libraries, pipelines, and APIs for ML researchers. Core tech: Python, TensorFlow, PyTorch, scikit-learn.
Develop, fine-tune, and deploy LLMs and ML systems for a B2B SaaS org-chart platform, building RAG pipelines, MCP servers, and Python microservices integrated into the web and cloud stack.
Data Engineer building and maintaining data infrastructure, ETL pipelines, and analytics platforms for AI-powered defense and national security products, using Python, SQL, and AWS.
Senior AI/ML engineer designing production-grade data pipelines and AI services using Python, pandas, scikit-learn, LLMs, FastAPI, and SQL, on-site 3 days/week in Montreal within Agile squads.
Staff Data Scientist leading the Fuel Detection Model, applying ML and remote sensing to satellite/environmental data to estimate vegetation structure, fuel loads, and wildfire risk for utility partners.
Part-time AI/ML engineer builds, trains, and deploys models using Python and frameworks like TensorFlow/PyTorch to solve government data challenges.
Alt is unlocking the value of alternative assets, starting with the $5 B trading-card market. We let collectors buy, sell, vault, and finance their cards in one place and we are backed by leaders at Stripe, Coinbase,…
This is an apprenticeship role for a Data Scientist/AI Engineer to develop machine learning models and predictive solutions within a financial risk department. The position involves the full data science lifecycle, from data exploration and feature engineering to model deployment and monitoring.
Senior Forward Deployed Software Engineer on ServiceNow's Applied AI team, building and deploying production LLM-powered applications end-to-end for strategic enterprise customers in London, spanning backend services, orchestration pipelines, and front-end integrations.
Machine Learning Engineer at Cinder building classification pipelines, confidence cascading, and model training/serving infrastructure for a trust & safety platform, using Python, PyTorch, scikit-learn, XGBoost, and LLMs.
Build and scale ML-driven dispute optimization systems, including training, deploying, and monitoring models, plus real-time data pipelines and feature stores for Checkout.com’s fintech platform.
A Data Scientist II designs and deploys AI models for customer engagement, partnering with clients to integrate data pipelines and reinforcement learning systems using Python, SQL, and ML libraries.
Entry-level Data Scientist for Dec 2026/May 2027 grads at an auto-lending company, building predictive models and translating data insights into business strategies using Python, R, SQL, and ML libraries like XGBoost and scikit-learn.
Управление рисков Индийского направления Сбера в поисках экспертов в области Data Science. Наша команда занимается построением передовых моделей в направлении корпоративного кредитования для Индийского филиала Сбера,…
About the Opportunity Solaris is seeking a mid-level Data Scientist to support turbine operations and engineering reliability efforts. This role bridges data engineering, statistical/ML modeling, and turbine domain…
Build and maintain scalable MLOps infrastructure on AWS to automate ML model training, deployment, and monitoring for a B2B sales-intelligence platform.
Design and deploy AI/ML systems for ICS/xOT cybersecurity, building threat detection and automation models in cloud and on-prem environments using Python, PyTorch/TensorFlow, and Kubernetes.
Design and deploy AI/ML systems for industrial cybersecurity, focusing on threat detection and automation in ICS/xOT environments using Python, ML frameworks, and Kubernetes.
Lead a team of software engineers building AI/ML models and platforms for Conga’s products, including feature stores, model training, and monitoring pipelines.
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