Description :
ML Model Development & Optimization :
- Experience in developing and implementing generative AI models and algorithms.
- Collaborate with Data Scientists to understand business problems, explore data, develop, train, and evaluate machine learning models (e.g., supervised, unsupervised, deep learning, reinforcement learning).
- Optimize models for performance, efficiency, and interpretability.
End-to-End ML Application Development :
- Lead the design, development, and deployment of machine learning models and intelligent systems into production environments, ensuring they are robust, scalable, and performant.
Software Design & Architecture :
- Apply strong software engineering principles to design and build clean, modular, testable, and maintainable ML pipelines, APIs, and services.
- Contribute significantly to the architectural decisions for our ML platform and applications.
Data Engineering for ML :
- Design and implement data pipelines for feature engineering, data transformation, and data versioning to support ML model training and inference.
Performance & Scalability :
- Identify and resolve performance bottlenecks in ML systems.
- Ensure the scalability and reliability of deployed models under varying load conditions.
Collaboration & Mentorship :
- Work closely with cross-functional teams including Data Scientists, Software Engineers, Product Managers, and DevOps to integrate ML solutions seamlessly into our products.
- Potentially mentor junior engineers on best practices in ML engineering and software design.
Research & Innovation :
- Stay abreast of the latest advancements in machine learning, MLOps, and related technologies.
- Propose and experiment with new techniques and tools to improve our ML capabilities.
Documentation :
- Create clear and comprehensive documentation for ML models, pipelines, and services.
Required Qualifications :
Education :
- Masters degree in computer science, Machine Learning, Data Science, Electrical Engineering, or a related quantitative field.
Experience :
- 10+ years of professional experience in Machine Learning Engineering, Software Engineering with a strong ML focus, or a similar role.
Good to have Programming Skills :
- Proficiency in Python, including experience with writing production-grade, clean, efficient, and well-documented code.
- Experience with other languages (e.g., Java, Go, C++) is a plus.
Strong Software Engineering Fundamentals :
- Deep understanding of software design patterns, data structures, algorithms, object-oriented programming, and distributed systems.
Must have Machine Learning Expertise :
- Solid theoretical and practical understanding of various machine learning algorithms.
- Proficiency with ML frameworks such as PyTorch, Scikit-learn.
- Experience with feature engineering, model evaluation metrics, and hyperparameter tuning.
Data Handling :
- Experience with SQL and NoSQL databases, data warehousing concepts, and processing large datasets.
Problem-Solving :
- Excellent analytical and problem-solving skills, with a pragmatic approach to delivering solutions.
Communication :
- Strong verbal and written communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
