Remote AI/ML Engineer II

Description:

• As an AI/ML Engineer, you will be responsible for designing, developing, and deploying AI and ML solutions that drive business value and innovation.
• You will work on cutting-edge machine learning models, including Generative AI, Large Language Models, and Deep Learning architectures.
• Your role will involve optimizing, fine-tuning, and scaling these models to meet business and performance objectives.
• You will collaborate closely with cross-functional teams, including data scientists, engineers, and product teams to integrate AI-powered solutions into products and services.
• Essential functions include developing, optimizing, and deploying machine learning and deep learning models, designing scalable AI solutions, fine-tuning models on large datasets, and collaborating with various teams.
• You will work with healthcare and claims data to build high-performance AI systems and develop MLOps pipelines for training, deploying, and monitoring AI models.
• Troubleshooting and resolving AI/ML engineering challenges will be part of your responsibilities, ensuring models perform effectively in production.
• Staying up-to-date with advancements in Generative AI, LLMs, and deep learning is crucial for continuously improving AI solutions.
• You will document AI/ML workflows, methodologies, and best practices for internal knowledge sharing.

Requirements:

• A Bachelor's or Master's degree in a quantitative field such as Computer Science, Data Science, or related disciplines is required.
• A minimum of 3+ years of experience in a data science/ML role, with a proven track record of delivering impactful solutions in a production environment is necessary.
• Proficiency in programming languages like Python, R, and SQL, with experience in building scalable and efficient ML/NLP workflows is essential.
• A deep understanding and hands-on experience in Machine Learning, Deep Learning, and Natural Language Processing is required.
• Experience working with state-of-the-art Generative AI models, including model fine-tuning and evaluation techniques is necessary.
• Knowledge of data management, including data pre-processing, augmentation, and generation of synthetic data is required.
• Familiarity with cloud computing and deployment for managing AI applications on platforms like AWS, Google Cloud, or Microsoft Azure is essential, including understanding containerization technologies like Docker and orchestration tools like Kubernetes.

Benefits:

• The position offers the opportunity to work on innovative AI and ML solutions that have a significant impact on business operations.
• You will collaborate with a diverse team of professionals, enhancing your skills and knowledge in a dynamic environment.
• The role provides a chance to stay at the forefront of advancements in AI technology, contributing to your professional growth.
• You will have the opportunity to document and share best practices, fostering a culture of continuous learning and improvement within the organization.