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You must be familiar with image processing, machine vision, and data engineering, and even better if you are interested in 3D rendering, deep learning, and computer graphics.
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Wells Fargo is seeking a Lead Software Engineer to join our Technology organization and be part of our Chief Technology Office (CTO) team. 3+ years of Kubernetes, Prometheus, Open Telemetry, Time Series Metrics, Capacity, Big Data, Machine Learning, or Synthetics monitoring tools experience.
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Our generative AI-powered products are bringing joy back to the practice of medicine, and we’re looking for a security-minded fullstack software engineer to join our growing US-based engineering team.
$180,000 - $205,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Leverage software engineering, machine learning, data science and data engineering techniques, sourcing and using a wide range of data types as you go, to enhance our platform's capabilities and deliver innovative solutions to our customers.
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Whether it's holding a PhD-level deep dive into understanding fairness and underlying bias in machine learning models, debating the merits of a Scandinavian design philosophy in our UI/UX, or writing responses for Medicare rules to influence U.S. health policy, we prioritize sharing our findings across the team and helping each other be successful.
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The App Dev team is hiring a Principal Software Engineer – Data, Microsoft Fabric to help build the v1 of SaaS-ified Data API and reusable custom business logic to build Trans-analytics applications in Microsoft Fabric.
$133,600 - $282,200 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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You will leverage your expertise in machine learning, deep learning, generative AI techniques, and software engineering principles to design, implement, optimize, and deploy these applications, ensuring seamless integration with existing workflows and infrastructure.
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We are looking for a Senior/Principal Software Engineer with a strong passion for innovation in distributed machine learning infrastructure. Distributed computing, parallel processing, cluster computing, scalability, multi-node architecture, data partitioning, load balancing, high-performance computing (HPC), fault tolerance, model parallelism, data parallelism, Horovod, PyTorch DDP, TensorFlow Distributed, machine learning infrastructure, cloud-based ML, GPU/CPU collaboration.
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Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action.
$150,000 - $250,000Full-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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The Enterprise Model Platform team in the Machine Learning Experience (MLX) organization supports a hosted internal Jupyter Notebook system running critical infrastructure for modeling and exploratory analysis across Capital One. You will get an opportunity and exposure to the thousands of models being trained on the notebook platform by myriad users across Capital One and dive deep into the unique engineering challenges we have around data access, security and scale.
$201,400 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, natural language processing or other ML discipline. Proficiency in code and system health, diagnosis and resolution, and software test engineering.
$136,000 - $200,000 a yearFull-timeExpandApply NowActive JobUpdated 27 days ago - UpvoteDownvoteShare Job
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2+ years of experience with artificial intelligence (AI), data science, ML engineering, data research, software engineering, or data analytics. Experience with project work in deep learning, computer vision, NLP, or chatbot development.
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Develop solutions that iterate orders of magnitude with higher efficiency, efficiently leverage orders of magnitude and more data, and explore state-of-the-art deep learning techniques.
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Technical experience in Machine Learning Engineering/Data Science or Software Development with recent coursework in ML/DS. Machine Learning Engineer. Work with a variety of different types, sources, and volumes of data by scraping, cleaning, extracting, and providing assessment to guide a viable machine learning solution.
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This role requires a combination of software engineering, systems engineering, and a deep understanding of machine learning operations (MLOps). The engineer will collaborate closely with machine learning scientists and data engineers to ensure the infrastructure meets the computational and data handling demands of the next generation of foundation model research and development.
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data software engineer engineering deep learning jobs Title: engineer in New York, NY
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