Software Engineer - Python Machine Learning Engineer

Job Description

As a Software Engineer with a focus on Machine Learning (ML) and Natural Language Processing (NLP), your role will involve designing, developing, and implementing ML and NLP models and solutions. You will be responsible for building, fine-tuning, and deploying Large Language Models (LLMs) and Generative AI (GenAI) applications. Your key responsibilities will include writing, maintaining, and optimizing Python code for ML and NLP projects, working with databases to collect, clean, and manage datasets for model training and evaluation, as well as deploying ML models and Python applications on public cloud platforms such as Azure or AWS. Additionally, you will collaborate with cross-functional teams to define business requirements and deliver solutions. It would be beneficial if you have experience supporting and implementing best practices for LLMOps, including monitoring and lifecycle management of LLM and GenAI models.To excel in this role, you should have a minimum of 2 years of relevant experience in machine learning, NLP, or AI solution development. Proficiency in Python programming with at least 2 years of hands-on experience is required. You should also possess practical experience of 2 years in building and deploying ML/NLP solutions, with at least 1 year of hands-on experience working with Large Language Models (LLMs) and Generative AI (GenAI) technologies. Experience working with modern databases (SQL/NoSQL) and cloud deployment of ML models or Python applications on Azure or AWS is essential. Familiarity with LLMOps tools or frameworks for managing LLM and GenAI models would be considered a plus.In addition to the technical qualifications, preferred skills for this role include familiarity with major ML/NLP libraries such as scikit-learn, TensorFlow, PyTorch, spaCy, and Hugging Face Transformers. An understanding of software engineering best practices, version control, and model lifecycle management is important. Strong analytical and problem-solving skills, as well as effective communication and teamwork abilities, are also desired traits for this position. As a Software Engineer with a focus on Machine Learning (ML) and Natural Language Processing (NLP), your role will involve designing, developing, and implementing ML and NLP models and solutions. You will be responsible for building, fine-tuning, and deploying Large Language Models (LLMs) and Generative AI (GenAI) applications. Your key responsibilities will include writing, maintaining, and optimizing Python code for ML and NLP projects, working with databases to collect, clean, and manage datasets for model training and evaluation, as well as deploying ML models and Python applications on public cloud platforms such as Azure or AWS. Additionally, you will collaborate with cross-functional teams to define business requirements and deliver solutions. It would be beneficial if you have experience supporting and implementing best practices for LLMOps, including monitoring and lifecycle management of LLM and GenAI models.To excel in this role, you should have a minimum of 2 years of relevant experience in machine learning, NLP, or AI solution development. Proficiency in Python programming with at least 2 years of hands-on experience is required. You should also possess practical experience of 2 years in building and deploying ML/NLP solutions, with at least 1 year of hands-on experience working with Large Language Models (LLMs) and Generative AI (GenAI) technologies. Experience working with modern databases (SQL/NoSQL) and cloud deployment of ML models or Python applications on Azure or AWS is essential. Familiarity with LLMOps tools or frameworks for managing LLM and GenAI models would be considered a plus.In addition to the technical qualifications, preferred skills for this role include familiarity with major ML/NLP libraries such as scikit-learn, TensorFlow, PyTorch, spaCy, and Hugging Face Transformers. An understanding of software engineering best practices, version control, and model lifecycle management is important. Strong analytical and problem-solving skills, as well as effective communication and teamwork abilities, are also desired traits for this position.

Keyskills :
PythonMachine LearningNatural Language ProcessingDatabasesLarge Language Models LLMsGenerative AI GenAI