Associate Engineer - Machine Learning

Associate Engineer - Machine Learning

As the Associate Engineer - Machine Learning, you will be responsible for bridging the gap between data analysis and full machine learning (ML) engineering. You will be accountable for contributing to production ML systems under guidance from senior team members. You will build and improve models, run experiments, and help operationalize ML with guidance from senior team members.

Responsibilities:

• Develop improvements to ML models to generate new content using ML algorithms in a secure, well-tested, and performant way
• Build and test ML models under supervision of senior engineers
• Implement algorithms from documentation and examples, modifying and extending existing code
• Train, evaluate, and optimize ML models for moderate-scope problems
• Work with highly complex data for feature development using ML models; collect, clean, and organize large datasets for analysis, ensuring data accuracy and quality
• Perform data preprocessing, feature engineering, and exploratory data analysis; analyze data patterns and extract meaningful insights to inform model development
• Collaborate with product managers, engineers, data scientists, and other stakeholders; work closely with senior team members to understand project requirements and translate them into technical solutions
• Participate in code reviews and maintain internal standards for style, maintainability, and best practices; document development processes, findings, and results for team knowledge sharing
• Ship small features and improvements with guidance and support from team members
• Assist with model deployment and monitoring in production environments; run tests and experiments to evaluate AI system functionality and efficiency
• Monitor model performance and address issues like drift and accuracy degradation

Qualifications:

• Bachelors Degree – Data Science, Machine Learning, Computer Science Statistics, Mathematics, or related quantitative field required; Masters Degree preferred
• 1 year of professional experience in machine learning, or data science, or related technical field, with 1 year hands-on experience with machine learning algorithms and frameworks (TensorFlow, PyTorch, scikit-learn); Or Master's in Machine Learning, Computer Science, Data Science, Statistics, Mathematics, or related quantitative field
• Competent with Python, SQL, and Git/GitHub programing languages
• Understanding of supervised and unsupervised learning algorithms
• Experience with model evaluation techniques (cross-validation, metrics, performance assessment)
• Experience with feature engineering and data preprocessing and statistical analysis and probability concepts
• Experience with Scikit-learn for traditional ML algorithms
• Experience with TensorFlow OR PyTorch for deep learning (at least one framework)
• Familiar with Pandas and NumPy for data manipulation and analysis and Matplotlib/Seaborn for data visualization
• Ability to explain technical concepts to non-technical stakeholders
• Technical experience across programming, data analysis, or software development preferred
• Experience in data engineering, analytics, or software development roles preferred
• Industry specific knowledge (Supply Chain) preferred
• Experience with AWS, Google Cloud, or Azure cloud ML services preferred
• Ability to travel 0% - 25%