Key Responsibilities:
Develop, optimize, and deploy machine learning algorithms and models using C++.
Work closely with data scientists and other engineers to integrate machine learning models into production environments.
Design and implement scalable, high-performance solutions for processing large datasets in real-time.
Collaborate with cross-functional teams to understand business needs and translate them into effective machine learning solutions.
Write clean, efficient, and well-documented code while maintaining coding standards.
Optimize model performance, conduct hyperparameter tuning, and implement techniques such as model ensembling, feature engineering, and data augmentation.
Stay up-to-date with the latest research and advancements in machine learning and artificial intelligence.
Troubleshoot and debug complex problems to improve system performance and reliability.
Contribute to the creation and maintenance of an effective machine learning development pipeline.
Required Skills and Experience:
Bachelor's or Master's degree in Computer Science, Electrical Engineering, Mathematics, or a related field.
Strong proficiency in C++, including experience with advanced features like multi-threading, memory management, and optimization for high-performance computing.
Solid understanding of machine learning concepts, including supervised and unsupervised learning, neural networks, decision trees, regression, classification, clustering, and deep learning.
Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn, etc.) and integrating them into C++ projects.
Familiarity with software design patterns, version control systems (Git), and continuous integration tools.
Experience working with large datasets and performing data preprocessing, cleaning, and transformation.
Strong problem-solving skills and the ability to think critically about algorithm optimization and real-world application.
Knowledge of performance optimization techniques for machine learning models in C++.
Preferred Qualifications:
Experience with GPU programming (CUDA, OpenCL) for accelerating machine learning workloads.
Familiarity with cloud platforms and distributed computing frameworks (e.g., AWS, Google Cloud, Apache Spark).
Knowledge of parallel computing and high-performance computing techniques.
Exposure to image processing, NLP, or other specialized machine learning domains.
Contribution to open-source machine learning projects or research papers.
Equal Opportunity Employer
We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.