Machine Learning Engineer

Job Description

As an Associate Machine Learning Engineer / Data Scientist, you will contribute to the advancement of research projects in artificial intelligence and machine learning. Your responsibilities will encompass areas such as large language models, image processing, and sentiment analysis. You will work collaboratively with development partners to incorporate AI research into products such as Digital Assistant and Document Capture. Essential Duties: Model Development : Assist in designing and implementing AI/ML models. Contribute to building innovative models and integrating them into existing systems. Fine-tuning Models : Support the fine-tuning of pre-trained models for specific tasks and domains. Ensure models are optimized for accuracy and efficiency. Data Clean-up : Conduct data analysis and pre-processing to ensure the quality and relevance of training datasets. Implement data cleaning techniques. Natural Language Processing (NLP) : Assist in the development of NLP tasks like sentiment analysis, text classification, and language understanding. Large Language Models (LLMs) : Work with state-of-the-art LLMs and explore their applications in various domains. Support continuous improvement and adaptation of LLMs. Research and Innovation : Stay updated with advancements in AI/ML, NLP, and LLMs. Experiment with new approaches to solve complex problems and improve methodologies. Deployment and Monitoring : Collaborate with DevOps teams to deploy AI/ML models. Implement monitoring mechanisms to track model performance. Documentation : Maintain clear documentation of AI/ML processes, models, and improvements to ensure knowledge sharing and collaboration. Basic Qualifications: Educational Background Programming and Tools Experience 1-2 years of total industry experience Minimum 6 months experience in ML Data Science Skills Problem-Solving and Analytical Skills Good oral and written communication skills. Bachelor s or Master s degree in Computer Science, Electrical Engineering, Mathematics, Statistics or a related field. Specialization or coursework in AI, ML, Statistics Probability, DL, Computer Vision, Signal Processing, or NLP/NLU is a plus. Proficiency in programming languages commonly used in AI and ML, such as Python or R querying languages like SQL. Experience in Cloud computing infrastructures like AWS Sagemaker or Azure ML for implementing ML solutions is highly preferred. Experience with relevant libraries and frameworks, such as scikit-learn, Keras, TensorFlow, PyTorch, or NLTK is a plus. This role offers a great opportunity to work with cutting-edge AI/ML technologies and contribute to innovative projects in a collaborative environment.