Senior Machine Learning Engineer

2 days ago


India FIFTYFIVE TECHNOLOGIES Full time

Job Description : We are looking for a dynamic and driven Machine Learning Engineer with expertise in building and fine-tuning Large Language Models (LLMs) and a keen interest in expanding their skills in MLOps. The ideal candidate will have 4 years of experience in designing and deploying machine learning models, a strong understanding of NLP and deep learning frameworks, and a proactive approach to learning and adopting MLOps practices for scalable and reliable model : - Develop, fine-tune, and evaluate Large Language Models (LLMs) such as GPT, BERT, and other transformer based architectures. - Apply advanced NLP techniques for tasks like text classification, summarization, question answering, and more. - Preprocess, clean, and augment large datasets, ensuring the quality and relevance of training data. - Implement optimization techniques to improve model efficiency and reduce computational costs. - Stay updated on cutting-edge advancements in LLMs and integrate state-of-the-art methodologies into model development. - Experiment with prompt engineering and fine-tuning techniques to optimize LLM performance for specific use cases. - Collaborate with cross-functional teams to brainstorm and implement innovative AI-driven solutions. - Collaborate with MLOps engineers to learn and contribute to the deployment of machine learning models into production environments. - Build and maintain APIs for integrating ML models into applications using frameworks like FastAPI or Flask. - Learn and implement model monitoring and governance frameworks to ensure model reliability and ethical compliance. - Design data pipelines for feature engineering and real-time data processing. - Collaborate with data engineers to automate data ingestion workflows and maintain high-quality datasets. - Work on foundational MLOps tasks like model versioning, artifact tracking, and performance monitoring under guidance from experienced team members. Requirements : - Hands-on experience with Large Language Models (LLMs) and deep learning frameworks like TensorFlow, PyTorch, and HuggingFace Transformers. - Strong understanding of Natural Language Processing (NLP) concepts, such as tokenization, embeddings, and transfer learning. - Proficiency in Python and a willingness to learn tools like MLflow, KFP, and other MLOps frameworks. - Eager to expand knowledge in MLOps practices, including automation, deployment pipelines, and monitoring systems. - Effective problem-solving and communication skills to work collaboratively in a team-oriented environment. - Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field. - Familiarity with cloud platforms such as Azure, AWS, or GCP for model deployment and scaling. - Basic knowledge of DevOps tools like Docker and Kubernetes, with a willingness to develop these skills further. - Exposure to data visualization tools like Looker Studio or Power BI- for presenting model insights. (ref:hirist.tech)



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