Sr Machine Learning Engineer
2 weeks ago
About the Role
We are currently seeking a highly skilled and experienced Sr. Machine Learning engineer to join our dynamic and innovative team. The ideal candidate will possess a deep understanding of machine learning frameworks, proficiency in SQL and data pipelines, and expertise in testing and deploying models. The position will play a crucial role in the design, implementation and management of scalable ML models. Come join us in shaping the future of our organization's AI-driven success.
Primary Responsibilities:
Design, build, and deliver production-ready ML models and components to solve sophisticated financial business problems. Apply expertise in machine learning to influence design decisions, including: model selection, data and feature selection, model training and hyperparameter tuning, and model validation. Write and test application code, develop and validate ML models, and automate testing and deployment pipelines. Train and fine-tune models using large datasets to achieve high performance and accuracy. Evaluate model performance using appropriate metrics and provide insights for continuous improvement. Deploy and monitor ML models ensuring scalability, efficiency, and maintainability. Retrain and maintain models to ensure continued effectiveness and address any data drift or performance degradation. Ensure all code is well-architected, modular, clearly documented, and written to reduce vulnerabilities and maintainability costs. Optimally communicate with all partners, including presenting technical findings and recommendations.About You
7+ years of professional experience in software development involving large-scale, real-time distributed systems. 3+ years of hands-on experience in developing and deploying machine learning models into production environments. Strong software engineering skills for developing scalable, modular, production-ready machine learning solutions. Required expertise in Python, OOP fundamentals, and deep learning frameworks like TensorFlow, PyTorch and Keras. Proficiency in data wrangling techniques, including data cleaning, normalization, feature extraction, and embedding. Experience with designing and implementing deep learning models (CNN, RNN) and transformer architectures. Strong SQL skills, ideally with experience in Snowflake. Proficiency in Spark/Databricks for processing large datasets. Proficiency in containerization tools (e.g. Docker) and orchestration systems (e.g. Kubernetes). Strong ability to write production-quality code that meets industry standards for code maintainability, reusability and version control. Strong understanding or experience with cloud platforms like AWS, Azure, or GCP. Experience with MLOps tools like Kubeflow/MLFlow or similar. Familiarity with version controls systems like Git. Bachelor's degree in Computer Science (or related field) or equivalent work experience.-
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