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If you've used Disney+, Peacock, or other top streaming platforms, you've already benefited from Conviva's technology.
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We are a growing subsidiary of a large public company that is hiring a talented Lead ML Engineer / Senior Machine Learning Engineer! 100% REMOTE Senior ML Engineer / Lead Machine Learning Engineer Needed for Growing Subsidiary of a Large Public Company.
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Experience with frameworks and libraries for machine learning & AI such as scikit-learn, HuggingFace, PyTorch, Tensorflow/Keras, MLlib, etc. 5+ years of practical experience in building, evaluating, scaling, and deploying machine learning pipelines with Python, preferably within the AWS ecosystem.
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Ability to design, train, and evaluate machine learning and AI models while adhering to best practices including model selection, validation, bias/variance tuning, performance assessment, sensitivity analysis, dimensionality reduction, etc.
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Experience in assessing and implementing new data tools to enhance the machine learning stack. Familiarity with Snowflake, Monte Carlo, RDS, DynamoDB, Kafka, Fivetran, dbt, Airflow, Docker, Kubernetes, EMR, Sagemaker, DataDog, PagerDuty, Atlan, Data Observability tools and Data Governance tools.
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Industrial/academic experience advancing the state-of-the-art machine learning-based research through demonstrable, verifiable technical results in their technical domain area (e.g., NLP, CV, etc.
$220,900 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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100% REMOTE Senior ML Ops Engineer / Lead Machine Learning Engineer Needed for Growing Subsidiary of a Large Public Company! Senior Machine Learning Operations Engineer. A modern productivity toolset to get work done: Slack, Miro, Loom, Lucid, Google Docs, Atlassian and more.
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Qualifications We DesireMaster’s degree in Computational Biology, Computational Bioengineering, Machine Learning, Statistics, Computer Science, Mathematics, or a related field. Knowledge and experience developing and applying algorithms in one or more of the following machine learning areas/tasks: deep learning, unsupervised feature learning, zero- or few-shot learning, active learning, transformer-based language modeling, multimodal learning, ensemble methods.
$245,544 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Adoption and Surrogacy Assistance Plan! Experience with orchestrating complex workflows and data pipelines using like Airflow or similar tools. Completed BS, MS, or PhD in Computer Science, Mathematics, Statistics, Data Science, Engineering, Operations Research, or other quantitative field.
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How you’ll make an impact: As a Staff ML Ops Engineer at SiriusXM, you will be a key player in our Data Platform Team. Your role will be pivotal in deploying, managing, and optimizing machine learning (ML) models, leveraging advanced tools like Databricks and MLFlow.
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Knowledge in domains such as recommender systems, fraud detection, personalization, and marketing science. Experience with Git, CI/CD pipelines, Docker, Kubernetes. Experience with building batch and streaming pipelines using complex SQL, PySpark, Pandas, and similar frameworks.
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5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
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Experience with developing data APIs, Microservices and event driven systems to integrate ML systems. Work from home / work remote 100%! This Jobot Job is hosted by: Reed Kellick. Strong programming skills in Python and understanding of core computer science principles.
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Utilize expertise in computational biology, machine learning, and bioinformatics to develop and optimize algorithms and models for the analysis of high-dimensional biological data. A Ph. D. or equivalent in computational biology, bioinformatics, machine learning, or a related field is preferred.
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Demonstrated expertise in machine learning, deep learning, and NLP, with a strong portfolio in large language models like GPT-3, BERT, and RAG.Advanced proficiency in Python, with hands-on experience in ML libraries and frameworks such as TensorFlow and PyTorch.
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