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Machine Learning Engineer

498261-Gtar Quantum Comp Namr
Full-time
On-site
New York, United States
$128,250 - $195,000 USD yearly
Description

The mission of the Digital Intelligence team is to leverage large-scale computation, substantial datasets, and machine learning to enhance our most crucial customer products across a broad spectrum. We manage a wide array of impactful products and services, reaching countless customers and households. We place high value on our customers' direct feedback and employ a truly agile methodology to incorporate improvements that enhance user experiences.


As a Machine Learning Engineer in the Digital Intelligence team, you will leverage large-scale computation, substantial datasets, and machine learning to enhance our most crucial customer products across a broad spectrum. Your expertise will promote the team to solve complex relevance and ranking problems, develop scalable features, and manage ML Ops for building innovative systems that benefit our customers across all lines of business.


Job Responsibilities:


*  Oversee the analysis of complex datasets to inform decisions on real-world applications.
* Lead the development and implementation of models and algorithms to enhance existing systems, processes, and products. 
* Supervise data analysis activities and ensure effective visualizations are provided.
* Ensure the writing and deployment of software code in production systems is efficient and meets standards.
* Anticipate risks associated with machine learning solutions and prediction/classification systems and strategize mitigation. 
* Communicate complex issues clearly and credibly to senior management and stakeholders. 
* Foster a transparent cross-functional work environment and influence peers and team members to uphold these standards.


Required qualifications, capabilities and skills:
* Master's degree in computer Science, Machine Learning or related field  with 3 years of relevant experience Ph.D in computer Science, Machine Learning, or a related field with 1 year of experience. 
* Expertise in one or more of the following areas: machine learning, Graph learning, recommendation systems, network analysis, natural language processing, Reinforcement learning, MLOps.
* Solid understanding of core CS concepts, including common data structures and algorithms.


Preferred qualifications, capabilities and skills:
* Experienced in conducting design and code reviews.
* Proficient in cloud environments such as AWS, GCP, or Azure.
* Experienced in managing and deriving insights from large, both unstructured and structured datasets.