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Youll have the opportunity to work alongside other talented engineers, CTO, and data scientists on cutting-edge big data, search, machine learning and analytics problems.
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Hands-on Experience in Big Data and cloud technologies tools, i.e. Hadoop, Hive, Iceberg, Kafka, Spark, Presto, Airflow, Elastic Search, Docker and Kubernetes. The Data Science and Machine Learning team at Lucid is on the mission to design, develop, and deploy AI solutions to help make safe and sustainable products and services on par with Lucid’s Luxury brand.
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Ideally 5+ years of hands-on design and development experience in several of the relevant technology areas (GitLab, Terraform, Azure, ADO, Azure Data Lake, Azure Kubernetes Service, Spark, Databricks etc.
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Assist in Problem Solving: Troubleshootplex issues related to machine learning model development and data pipelines and develop innovative solutions. Hands-on experience developing natural language processing (NLP) models, ideally with transformer architectures.
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Staying on top of emerging trends in generative AI and multi-modal LLM.Strong programming skills and hands-on experience using the following languages or deep learning frameworks: Python, PyTorch, or Jax. Strong problem-solving and communication skillsDescription: As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying state-of-the-art research in ML to tackle sophisticated data problems.
$170,700 - $300,200 a yearExpandUpdated 0 days ago - UpvoteDownvoteShare Job
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Implement and deliver high quality DevOps solutions for our new state of the art AI model deployment and execution platform using technologies like Gitlab, ADO, Terraform to deliver services such as Databricks, Kubernetes, Postgres, Azure Data Factory, Azure Cognitive Search.
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If you are intrigued by significant challenges in data engineering, distributed systems, and machine learning, and are keen on contributing to a groundbreaking technology platform, this role awaits you.
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Has prior experience in NLP/Machine Learning initiatives, and has strong data-grounding to guide investments. We are in search of a leader to scale our Data Science organization which encompasses ML and NLP engineers, Data Analysts, Computational Linguists, and Data Engineers to support our growing scale, and product offerings.
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Hands-on experience with data analytics and classical machine learning tools(like pandas, NumPy, scikit-learn)and deep learning frameworks(like Tensorflow, Lang Chain, Pytorch, Flask, Fast API.
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Whether you join our Statistics, Optimization, or Machine Learning teams, you’ll be challenged to harness Target’s impressive data breadth to build the algorithms that power solutions our partners in Marketing, Supply Chain Optimization, Search and Personalization rely on.
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Demonstrated hands-on programming skills in Python, SQL, Hadoop, Hive. Additional knowledge of Spark, Scala desired. Every scientist on Target’s Data Sciences team can expect to do modeling and data science, develop software/product with highly performant code, elevate Target’s culture, and apply retail domain knowledge.
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E, AWS and GCP) Strong verbal and written communication skills Ability to conduct meetings and make professional presentations, and explain complex concepts and technical material to non-technical users Experience with machine learning platform for search & discovery related rankings is a strong plus Pay & Benefits Our compensation reflects the cost of labor across several US geographic markets.
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End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark) 4+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning.
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Additionally, your hands-on experience with search and vector database technologies will facilitate the conception and optimization of robust and efficient solutions. Hands-on experience with building, implementing and optimizing search and vector database technologies such as Elastic, Vespa, Pinecone, Lucene, etc.
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Develop and distribute monthly reports for key stakeholders outlining performance, progress, and SearchLearn, Manage and Optimize Onsite Search ResultsGain a deep understanding of our on-site search engine, how the Machine Learning works and its capabilities.
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