Machine Learning Engineer

Job Description

90% Analytical and Development Support Design and implement machine learning solutions to address specific business needs. Develop and maintain machine learning infrastructure, including data pipelines, model training and deployment systems. Collaborate with cross-functional teams to deploy machine learning solutions to the RSS production environment. Continuously monitor and improve the performance of machine learning models over time. Stay up to date with the latest advancements and best practices in machine learning. Follow development standards to produce production quality machine learning solutions. Follow data privacy and security standards. 10% Other Duties as Assigned Participates in staff meetings and functions. May be assigned miscellaneous projects. Requirements Bachelors degree in Computer Science, Engineering, Mathematics, or Information Systems or equivalent combination of education and experience. 3+ years of professional experience as a machine learning engineer designing, developing, deploying and supporting machine learning models and platforms for medium to large sized projects. 3-5 years of professional machine learning experience preferred. Experience with the entire Software Development Life Cycle (SDLC) of deploying machine learning models to production in one or more domains, such as classification, Natural Language Processing (NLP), computer vision, recommendation systems, and forecasting. Experience translating business requirements to technical solutions and developing technical specifications and documentation for use in the development and prioritization of work. Oral, written and interpersonal skills to interact and communicate effectively and professionally with technical and nontechnical stakeholders. Experience implementing machine learning algorithms in Python such as linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), Naive Bayes, neural networks, clustering, dimensionality reduction, and natural language processing (NLP). Strong problem-solving skills and the ability to work independently or in a team environment. Experience with industry tools and platforms used to build scalable machine learning systems, such as Elasticsearch, Kubernetes, Docker, Redis, Apache Kafka, SQL, NoSQL, Infrastructure as Code (IaC), AWS Lambda, and/or Apache Spark. Experience building a CI/CD pipeline with Github Actions, TravisCI, or others. Experience with cloud computing platforms such as AWS, Azure, or GCP. Experience developing web applications in Javascript and/or mobile applications.

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