Senior ML Engineer

March 15

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Description

• Research and Development: Conduct research to explore state-of-the-art machine learning algorithms, stay updated on the latest advancements, and propose innovative solutions to tackle business challenges effectively • Model Development: Design, build, and optimize machine learning models and algorithms that can be deployed on various platforms and integrated into our products • Data Preprocessing: Prepare and clean datasets to ensure they are suitable for model training and validation, while addressing issues such as missing data and outliers • Model Training and Evaluation: Train machine learning models using vast datasets, validate their performance, and fine-tune hyperparameters to achieve optimal accuracy and generalization • Integration and Deployment: Collaborate with software engineering teams to integrate machine learning models into production systems and ensure seamless deployment in real-world environments • Performance Monitoring: Implement monitoring and logging mechanisms to track model performance in production and detect potential anomalies or degradation in accuracy • Continual Improvement: Conduct thorough analysis of model performance, identify areas for improvement, and iterate on existing models to enhance their effectiveness • Collaboration: Collaborate with cross-functional teams, including data scientists, software engineers, product managers, and stakeholders, to define project requirements and ensure alignment with business objectives • Documentation: Create clear and comprehensive documentation for models, algorithms, and implementation processes, enabling easy knowledge transfer within the team • Innovation and Research Contribution: Stay up-to-date with the latest trends and advancements in machine learning, participate in research discussions, and contribute to the company's intellectual property through patent filings and publications

Requirements

• Education: Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field. A Ph.D. is a plus • Experience: Demonstrable experience in developing and deploying machine learning models in real-world applications. (7 years of experience, depending on the seniority level) • Programming Skills: Proficiency in programming languages like Python, R, or similar, along with experience in using machine learning libraries such as TensorFlow, PyTorch, or scikit-learn • Mathematics and Statistics: Strong understanding of linear algebra, calculus, probability, and statistics, coupled with the ability to apply these principles to machine learning problems • Deep Learning: Familiarity with deep learning techniques, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer models • Data Handling: Experience with data preprocessing, feature engineering, and data augmentation techniques to enhance model performance • Software Engineering: Understanding of software engineering principles, version control, and the ability to write clean, modular, and maintainable code • Problem-Solving: Analytical mindset with a proven ability to break down complex problems, develop innovative solutions, and troubleshoot issues effectively • Communication: Strong verbal and written communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders • Team Player: A collaborative approach to work, with a willingness to contribute to team success and a commitment to promoting a positive work environment

Benefits

• Base salary range for this position is $135,000 - $235,000 and is based upon years of experience that is commensurate with the level of the position • Robust equity program with significant upside potential • Benefits including medical, dental, vision, disability, life, and 401k