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Sybrin · 1 month ago

Intermediate Machine Learning Engineer (Hybrid)

United States

Full-time

Hybrid

Mid Level

3+ years exp

Sybrin is a leading IT software development company specializing in innovative solutions tailored to meet the evolving needs of businesses across various sectors. The role involves developing and implementing machine learning solutions, designing and deploying models, and enhancing the company's product offerings.

BankingFinancial ServicesInformation TechnologySoftware

Responsibilities

Designing and developing machine learning models and algorithms

Performing data preprocessing, data analysis and feature engineering

Evaluating model performance and tuning hyperparameters for optimization

Collaborating with data scientists, software engineers, and stakeholders to define project requirements

Implementing and deploying machine learning models into production

Conducting code reviews to ensure code quality and best practices

Debugging and resolving issues related to machine learning models and data pipelines

Creating and maintaining technical documentation for machine learning projects

Staying updated with the latest advancements in machine learning and data science

Qualification

Machine Learning FrameworksModel DevelopmentData ProcessingModel DeploymentAPIsCloud PlatformsVersion Control SystemsData LabellingData VisualizationAnalytical thinkingISO Standards KnowledgeProblem-solvingEffective communication

Required

Bachelor's degree in Computer Science, Data Science, Statistics, or a related field

Minimum of 3-5 years' experience

Experience with frameworks such PyTorch, TensorFlow, TensorFlow Light, Oynx and Scikit-learn

Generation of data sets, using data labelling tools such as Roboflow or CVat

Proficiency in using libraries such as Pandas, NumPy, and SciPy for data manipulation and analysis

Understanding of key machine learning and statistical algorithms including regression, classification, clustering and neural networks

Experience in developing, training, and evaluating machine learning models

Basic knowledge of deploying models using FastAPI and Docker

Understanding of creating RESTful APIs to integrate ML models into applications

Proficient in using Git and DVC for version control

Skills in using libraries such as Matplotlib, Seaborn, and Plotly

Some experience with the machine learning aspects of cloud services such as AWS, Google Cloud, or Azure

Experience with integrated development environments (IDEs) like PyCharm or VS Code

Analytical thinking

Problem-solving

Effective communication

Working knowledge of the principles in ISO 9001:2015 (Quality Management System), ISO/IEC 27001:2022 (Information security, cybersecurity, and privacy management System), ISO/IEC 27701:2019 (Privacy Information Management System), POPIA, GDPR