Overview of the Role
As a Senior Development Engineer in Applied Machine Learning, you will oversee the design and deployment of sophisticated machine learning models, leveraging your extensive expertise. Your role will involve architecting modules for system solutions and utilizing advanced programming techniques to solve complex problems.
You will lead the development of robust machine-learning algorithms. Your leadership will also extend to implementing large-scale machine learning solutions and ensuring their seamless integration into production environments, setting strategic directions and innovating within the field.
Job Responsibilities
- Develop and deploy machine learning models to address complex business challenges and improve real-world applications.
- Continuously enhance model performance through exploratory data analysis and by staying informed on the latest machine learning technologies.
- Lead the complete lifecycle of machine learning projects, from defining problems and preparing data to evaluating and deploying models.
- Design robust and scalable machine learning pipelines in collaboration with domain experts, integrating best industry practices.
- Implement cutting-edge machine learning techniques, including deep learning and natural language processing, to maintain a competitive edge
- Manage the integration and quality control of data across systems, and streamline the training and deployment of machine learning models.
- Automate and optimize machine learning workflows to ensure efficient model performance and integration into production environments.
- Enhance product development by creating features that leverage machine learning for better personalization and user experience.
- Strategically align machine learning initiatives with business goals to optimize product features and operational processes.
- Optimize internal processes through data analysis, and participate in all aspects of the model lifecycle, from feature engineering to monitoring deployed models.
Skills & Qualifications
- Bachelor’s or Master’s degree in Computer Science or any other analytically inclined field of study.
- Proven 5 - 8 years of experience as an Applied Machine Learning Engineer.
- Hands-on experience with Core Python and advanced Python features and libraries such as requests, TensorFlow, Keras, PyTorch, Pillow, Scrapy, Numpy, Pandas, Matplotlib, SQLAlchemy, Django, Flask, Twisted and FAST API.
- Deep knowledge in system design and architecture, with a strong command over design principles focused on Python.
- Hands-on experience with NLP, Transformer-based models, Large Multimodal Models (LMM), and Large Language Models (LLMs).
- Experience in working on large-scale data projects and deploying Machine Learning solutions into production environments.
- Involved in classification and clustering algorithms, including ensemble models like Random Forest and XGBoost.
- In-depth knowledge in Object-Oriented Programming (OOPs).
- Proficiency in using ORM tools like SQLAlchemy or Django ORM.
- Expertise in developing, integrating, and testing RESTful services.
- Understanding of system design principles for architectural roles.
- Hands-on experience in SQL and NoSQL Databases.
- Knowledge in debugging and using testing frameworks like pytest or unittest.
- Familiarity with data structures and algorithms.
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