Machine Learning Engineer

You will be joining a life sciences company that specializes in pharmaceutical regulatory solutions and utilizes AI to address intricate data challenges within specialized fields. As a Machine Learning Engineer, your primary responsibility will be to lead NLP-driven projects and contribute to the development of foundational AI models tailored for domain-specific applications. Your key tasks will involve designing and building machine learning systems in the Pharma Life Science domain, implementing relevant ML algorithms, conducting experiments, and keeping abreast of the latest advancements in the field. Your duties will include developing and refining machine learning models that focus on text analysis, data extraction, and NLP tasks. You will be involved in preprocessing and structuring large datasets to ensure high quality and consistency. Additionally, you will design and deploy efficient data pipelines to manage unstructured and semi-structured data sources effectively. You will collaborate with cross-functional teams to integrate machine learning models into production environments, ensuring their reliability and scalability. Furthermore, you will continuously test, evaluate, and optimize model performance to align with project requirements and user needs. To qualify for this role, you should possess 2-4 years of experience in a related field with a strong background in machine learning, particularly focusing on NLP and text-based data processing. Proficiency in ML frameworks such as PyTorch or TensorFlow, along with experience in NLP libraries like Hugging Face Transformers or SpaCy, is essential. You should have a solid understanding of data wrangling, feature engineering, and preparing datasets for model training. Knowledge of NLP models including BERT, GPT family, Transformers, etc., is required. Hands-on experience in deploying and optimizing machine learning models for production use, familiarity with cloud platforms (AWS, GCP, Azure), and version control systems like Git are important for this role. Strong problem-solving skills, a sense of ownership, and the ability to communicate complex concepts clearly are also key attributes that will contribute to your success in this position.,