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We're looking for a Machine Learning Engineer to join our Artificial Intelligence team and work with our team of data scientists to automate thetraining and evaluationofmodels within an Azure ecosystem.
Full-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Conducts advanced analytics leveraging predictive modeling, machine learning, simulation, optimization and other techniques. Master s degree with coursework in advanced Machine Learning techniques (Natural Language Processing, Deep Neural Networks, etc.
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As a Machine Learning Engineer, you'd be joining a talented and friendly team which loves to delight its customers with quality and robust code. Use off-the-shelf machine learning solution to provide simple initial solutions for fraud detection.
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The Role As a Machine Learning Engineer you will research, develop, and support the machine learning models that allow our devices to decode evidence like a detective and define how non-violent crime is eliminated.
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Velvetech constantly follows the Tech trends and actively cooperates with startups in such breakthrough areas as Machine Learning, the Internet of Things, Blockchain, FPGA, and AI. Many CHALLENGING and exciting projects with new opportunities and learning.
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And exciting projects with new opportunities and learning. We implement modern backend solutions that support microservices architecture with the following technologies: NET Core, Node.js, Java, SQL Server, PostgreSQL, MongoDB, Redis, RabbitMQ. For the web UI front-end development, we opt for React, or Angular, and for mobile development Swift, Kotlin, Java. Most of the systems are designed for cloud infrastructures like AWS, Azure, GCP, and heavily rely on Docker, Kubernetes while modern CI/CD is made using GitLab CI or TeamCity.
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We seek machine learning engineers with a passion for sports to implement, automate, and optimize the quantitative models that power our world-class sports intelligence platforms in baseball, basketball, cricket, football (American), hockey, soccer, and tennis.
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We are seeking a skilled and innovative Machine Learning Engineer to join our team. Proven experience as a Machine Learning Engineer or in a similar role. Model Development: Design, build, and deploy machine learning models to improve various aspects of our platform, including customer personalization, predictive analytics, and automated decision-making.
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Design, build, and deploy machine learning models to improve various aspects of our platform, including customer personalization, predictive analytics, and automated decision-making. Provide insights and guidance on best practices in machine learning, and contribute to the strategic direction of our technology.
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Proven ability to Formulate data science and machine learning strategies to align with business objectives. Advanced experience developing Machine Learning models or ML Ops processes.
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Strong understanding in the machine learning and data science technical ecosystems (e.g., Tensorflow, Pytorch, MLflow, Ray, LangChain, Data lake house (Databricks), Snowflake, SageMaker, Scikit-learn, etc.
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As a Machine Learning Automation Engineer on the Behavioral Automated Triage team, you will interrogate data at scale, perform data engineering, leverage deep learning models (i.e. foundation models and language models), and respond to the evolving data needs at Zoox.
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We're looking for someone who has a passion for building scalable machine learning and MLOps platforms using technologies such as Python, Databricks, Spark, AWS, Airflow, Terraform, etc.
$110,000 - $142,000 a yearFull-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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As a senior machine learning engineer will also mentor more junior engineers. Machine Learning Engineer, Sr. Leads development of computer vision and machine learning (ML) algorithms capable of detection, classifying, localizing, and tracking objects of interest from a variety of stationary and mobile sensor platforms.
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Machine Learning and Deep Learning: Good understanding of: ML algorithms like linear regression, logistic regression, etc., supervised, unsupervised, and reinforcement learning, AI Frameworks like TensorFlow, PyTorch, scikit-learn etc., Neural network, NLP, computer vision, and predictive analytics.
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