Position : ML / LLM Engineer + AWS
W2 only
Locations : USA -Delaware, New Jersey, Philadelphia
IFF Research & Development Complex (also where corporate IT is)
1515 NJ-36
Union Beach, NJ - 07735Experimental Station
200 Powder Mill Road
Wilmington, DE - 19803
Hybrid : 3 Days from Office
Job Overview:
We are looking for a skilled ML / LLM Engineer with strong expertise in AWS to join our innovative team. The ideal candidate will be responsible for designing, developing, and deploying machine learning models and large language models that drive impactful business solutions.Key Responsibilities: • Design, develop, and implement machine learning models and LLMs using AWS services such as Amazon SageMaker, AWS Lambda, and Amazon Comprehend.
• Collaborate with data scientists, engineers, and product teams to identify use cases and define requirements for ML solutions.
• Optimize and fine-tune models for performance, accuracy, and scalability.
• Conduct experiments and analyze model performance using appropriate metrics.
• Ensure seamless integration of ML solutions with existing applications and workflows.
• Monitor and maintain model performance in production environments, implementing necessary updates and improvements.
• Stay informed about the latest trends and advancements in machine learning, LLMs, and AWS technologies.Qualifications: • Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
• 3-5 years of proven experience as an ML Engineer or LLM Engineer, particularly with AWS platforms.
• Proficiency in AWS services for machine learning, including Amazon SageMaker and AWS Lambda.
• Strong programming skills in languages such as Python.
• 2-3 years of experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Hugging Face) and natural language processing techniques.
• Familiarity with data preprocessing, feature engineering, and model evaluation methods.
• Excellent analytical and problem-solving skills with a focus on detail and quality.Preferred Skills: • Experience with deploying and maintaining AI/ML models in production.
• Knowledge of MLOps practices and CI/CD pipelines.
• Understanding of ethical considerations in AI and machine learning.