AI/ML Engineer II

Summary

Join us as an AI/ML Engineer to design, develop, and deploy cutting-edge AI and ML solutions. You will work with Generative AI, Large Language Models, and deep learning, optimizing and scaling models to meet business objectives. Collaborate with cross-functional teams to integrate AI solutions into products and services. This role involves developing and deploying machine learning models, designing scalable AI solutions, fine-tuning models for improved performance, and collaborating with various teams. You will also work with healthcare and claims data, maintain MLOps pipelines, and troubleshoot AI/ML challenges. Staying current with advancements in AI is crucial. Documenting workflows and best practices is also a key responsibility.

Requirements

• Bachelors or Masters in a quantitative field such as Computer Science or Data Science or related disciplines
• Minimum of 3+ years’ experience in data science/ML role, with a track record of delivering impactful solutions in a production environment
• Proficiency in programming languages like Python, R, and SQL, with experience in building scalable and efficient ML/NLP workflows
• Deep understanding and hands on experience in Machine Learning, Deep Learning, and Natural Language Processing
• Experience in working with state-of-the-art Generative AI models, including model finetuning and evaluation techniques
• Data management knowledge, including data pre-processing, augmentation, and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models
• Cloud computing and deployment knowledge for deploying and managing AI applications on cloud platforms like AWS, Google Cloud, or Microsoft Azure. This includes understanding containerization technologies like Docker and orchestration tools like Kubernetes, which are important for scaling AI solutions

Responsibilities

• Develop, optimize, and deploy machine learning and deep learning models, including LLMs and Generative AI models
• Design and implement scalable, production-ready AI solutions that integrate into existing systems
• Fine-tune and evaluate models on large-scale datasets to improve accuracy, efficiency, and robustness
• Collaborate with software engineers, data scientists, and product teams to align AI models with business needs
• Work with healthcare and claims data to build high-performance AI systems
• Develop and maintain MLOps pipelines for training, deploying, and monitoring AI models
• Troubleshoot and resolve AI/ML engineering challenges, ensuring models perform effectively in production
• Stay up-to-date with advancements in Generative AI, LLMs, and deep learning to continuously improve AI solutions
• Document AI/ML workflows, methodologies, and best practices for internal knowledge sharing

Preferred Qualifications

• Problem solving for thinking outside the box to design and implement novel AI solutions when faced with unprecedented challenges
• Collaboration and communication for articulating technical details and project needs to technical and non-technical team members, including data scientists, software developers, and business stakeholders, and ability to influence leaders across functions and companies
• Continuous learning for keeping up the latest research, tools, and techniques in the rapidly evolving generative AI landscape
• Patience and persistence for staying motivated, even when facing setbacks
• Excellent interpersonal and communication skills, with strong written and verbal presentation
• Proven ability to take ownership and lead multiple engagements with minimal oversight
• Ability to synthesize complex concepts into understandable and actionable solutions
• Demonstrated expertise in Precision Products and Services with ability to recommend existing solutions and/or propose new products and services based on client need
• Ability to drive executive level conversation regarding business value
• Demonstrated cross-functional sales and business development success
• Passionate and confident communicator with ability to energize stakeholder decision-making