AI / Machine Learning Engineer

As an AI/ML Engineer, you will be at the forefront of 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 while ensuring they 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.

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.

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.

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.

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.

Ability to drive executive level conversation regarding business value

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Employment decisions are made without regard to race, color, age, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status or other characteristics protected by law.

If you are an individual with a disability and require a reasonable accommodation to complete any part of the application process or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, you may contact Precision Medicine Group

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