ML Engineer

Job Description

ML Engineer job profile Machine Learning is a field of artificial intelligence that focuses on developing systems that can learn and improve from experience. Machine Learning Engineers work on creating and implementing AI models and algorithms to solve complex problems. This role often involves working with large datasets, developing algorithms, and deploying models into production environments. ML Engineer job description We are seeking an enthusiastic and motivated Machine Learning Engineer with 1-3 years of experience to join our team. As a Machine Learning Engineer, you will be responsible for designing, building, and maintaining machine learning models with a focus on Generative AI, Large Language Models (LLMs), and Natural Language Processing (NLP). You will use your skills and knowledge to tackle real-world challenges and contribute to the advancement of AI technology. ML Engineer duties and responsibilities Design, develop, and implement efficient and scalable machine learning models and algorithms Work closely with software engineers to integrate ML models into production systems Implement and optimize NLP algorithms and pipelines Optimize and fine-tune existing models for improved performance Contribute to the research and implementation of state-of-the-art GenAI techniques Participate in the full machine learning lifecycle, from data preparation to model deployment Collaborate with cross-functional teams to identify and solve complex business problems using AI Stay up-to-date with the latest advancements in ML, especially in GenAI, LLMs, and NLP Document your work, including model architectures, experiments, and results Must have skills C++ Programming: Proficiency in writing efficient, modular, and maintainable C++ code, including knowledge of advanced features such as templates, STL, and memory management, and implementation of data structures, algorithms, object-oriented programming principles, and design Visual Studio: Experience using Visual Studio IDE for C++ development, including project management, debugging, and performance profiling. VC++ : Background in Visual C++, including building applications for Windows platforms, integrating with Windows APIs, etc Database Management: Experience working with relational databases (e.g., SQL Server, MySQL) and proficiency in writing efficient SQL queries, database design, and optimization. Good to have skills File System Knowledge: Understanding of different file systems such as FAT (File Allocation Table), APFS (Apple File System), and NTFS (New Technology File System), and their structures, features, and limitations. Low-Level APIs: Familiarity with low-level APIs for system-level programming, including filesystem APIs, device drivers, and system calls. Understanding of memory management, I/O operations, and concurrency control at a low level.