Machine Learning Engineer In-Office Job (full time)

ML Engineer position focusing on NLP and Large Language Models

Detailed Overview

Job Description: We are looking for a talented and enthusiastic Machine Learning Engineer to join our Data Science and Analytics team. This role involves working on a variety of Natural Language Processing (NLP) tasks, exploring modern Large Language Models (LLMs), and fine-tuning these models to enhance our platform's capabilities. Responsibilities: Design, develop, and deploy machine learning models and algorithms for NLP tasks. Explore and implement state-of-the-art techniques in LLMs and stay updated with the latest advancements in the field. Fine-tune and optimize LLMs for specific use cases relevant to our platform. Collaborate with cross-functional teams to integrate machine learning solutions into our product. Conduct data analysis and build models to extract insights from large datasets. Evaluate model performance and iterate to improve accuracy and efficiency. Document and share findings, methodologies, and best practices with the team. Requirements: Education: Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field. Experience: Proven experience as a Machine Learning Engineer or in a similar role. Skills: Required skills are as follows- Strong proficiency in Python and machine learning frameworks (e.g., TensorFlow, PyTorch). Experience with NLP and modern LLMs (e.g., Llama, Gemini, GPT, BERT). Familiarity with data preprocessing, feature engineering, and model evaluation techniques. Ability to work with large datasets and perform data analysis using tools like Pandas and NumPy. Excellent problem-solving skills and the ability to think critically. Strong communication skills and the ability to work collaboratively in a team environment. Preferred Qualifications: Experience with cloud platforms (e.g., AWS, GCP, Azure) for deploying machine learning models. Knowledge of big data technologies (e.g., Hadoop, Spark). Experience with version control systems (e.g., Git) and collaborative development platforms (e.g., GitHub).