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The Machine Learning Engineer will develop generative world models and interactive simulation environments to advance autonomous driving research. The role focuses on creating efficient, real-time models using Python and PyTorch to improve training and evaluation for self-driving systems.
This role involves building and scaling generative world models to produce synthetic data for autonomous driving research. You will bridge the gap between ML research and engineering by optimizing model architectures and integrating synthetic data into the training pipeline for driving models.
Design and deploy ML models directly onto custom hardware, co-architecting solutions with traders and engineers while optimizing for latency and resource constraints.
Build and optimize large-scale ML training and inference pipelines for low-latency trading systems using Python, CUDA, PyTorch/TensorFlow, and GPU acceleration.
Research and deploy ML models to generate trading signals and optimize portfolios, collaborating with quants and engineers using Python and PyTorch/TensorFlow.
Researcher builds deep-learning models to predict short-term market moves for high-frequency delta-one trading, using TensorFlow/PyTorch and collaborating with traders and engineers.
Research and implement ML models for global trading strategies, deploying solutions in equities, futures, and options markets using Python and frameworks like PyTorch.
Research intern designing ML models to analyze market data and inform trading strategies in equities, futures, and options.
Research and implement ML models for global trading strategies in equities, futures, and options markets using Python and PyTorch.
Research intern in Amsterdam and London building ML models to analyze market data and inform trading strategies for a global quantitative firm.
Machine Learning Research Intern developing and applying ML algorithms and predictive models to large-scale datasets for global trading strategies, using Python, PyTorch, TensorFlow, or JAX.
Designs and builds scalable data pipelines and AI architectures, deploys deep learning models, and leads statistical modeling for production systems using Python, PySpark, and ML frameworks.
Build and deploy LLM-powered AI agents and retrieval systems for a bank’s client-facing copilot, using PyTorch, LangChain, and RAG pipelines.
AI Engineer designing, building, and deploying production ML and Generative AI/LLM solutions across the full lifecycle using Python, PyTorch/TensorFlow, RAG pipelines, and MLOps practices.
Наша команда занимается управлением модельным риском, возникающим в результате некорректной работы моделей. Этот риск может приводить к финансовым и репутационным потерям. Главным образом, мы работаем с моделями на…
The researcher will develop and implement quantitative investment strategies for global equities by building machine learning models and analyzing large financial datasets. The role involves collaborating with portfolio managers to improve alpha signals and refine proprietary research systems.
Мы строим систему управления операционными рисками экосистемы Сбера на основе агентного ИИ. Если тебе тесно в роли просто сильного разработчика, а хочется вести за собой команду единомышленников, реализуя проекты…
AI/ML Engineer II 3-8 Years Experience JOB SUMMARY We are seeking a highly capable AI/ML Engineer II to serve as a strong individual contributor within our Artificial Intelligence and Automation team. The ideal…
Build and deploy AI solutions on Databricks and Azure, covering the full ML chain from data to monitoring with a focus on cost-efficient, production-grade systems.
ПриватБанк — є найбільшим банком України та одним з найбільш інноваційних банків світу. Займає лідируючі позиції за всіма фінансовими показниками в галузі та складає близько чверті всієї банківської системи країни. Ми…
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