Senior AI/ML Engineer

Summary

Join CareMessage, a technology non-profit, as a Senior AI/ML Engineer and contribute to improving health equity for millions. You will design, build, and deploy machine learning models and AI-powered systems to enhance decision-making on our platform. This role involves collaborating with a multidisciplinary team, leveraging large language models, and ensuring model performance and scalability. The ideal candidate possesses extensive experience in AI/ML engineering, particularly within healthcare, and a passion for using technology to improve healthcare outcomes. This is a fully remote position with a competitive salary and benefits package.

Requirements

• 5+ years as an AI/ML Engineer with a focus on healthcare AI/ML use cases
• 5+ years of experience with Python and machine learning frameworks such as scikit-learn, SparkML, TensorFlow, PyTorch, pandas, Hugging Face, etc
• Strong understanding of machine learning algorithms (e.g., supervised and unsupervised learning, natural language processing, reinforcement learning)
• Proven track record of applying ML techniques to healthcare data, particularly with natural language processing (NLP), Generative AI, and large language models (LLMs)
• Hands-on experience in training, tuning, and deploying models in production environments, including proficiency in advanced prompting techniques and fine-tuning LLMs for various use cases
• Hands-on experience deploying machine learning models in cloud environments (preferably GCP, but AWS or Azure are acceptable)
• Expertise in building and scaling end-to-end machine learning pipelines in production environments
• Familiarity with MLOps practices for model management and deployment
• Excellent communication skills to convey complex technical concepts to non-technical stakeholders and to collaborate effectively within a cross-functional team
• Strong expertise in data preprocessing, feature engineering, and model evaluation techniques
• Ability to translate business requirements and metrics into machine learning model specifications and solutions
• Applicants must be authorized to work in the United States on a full-time basis without sponsorship

Responsibilities

• Collaborate with engineers to develop, modify, and optimize machine learning models, including both generative AI (LLMs) and discriminative AI models, tailored to address specific business challenges
• Leverage large language models (LLMs) for applications such as text generation, text classification, and other AI-powered solutions
• Design and implement models for predictive analytics and classification tasks, ensuring high accuracy and reliability
• Design scalable, production-ready AI/ML solutions, taking models from initial concept through to deployment
• Monitor and maintain models post-deployment, making necessary adjustments to improve performance and address changing requirements
• Conduct experiments and fine-tune machine learning models to optimize their accuracy and overall performance
• Create high-level and detailed design plans for AI/ML production solutions, including selecting appropriate algorithms, data sources, infrastructure, and technologies that align with the organization's goals and constraints
• Design and implement scalable AI/ML pipelines that can efficiently handle production-level data and adapt to various use cases
• Ensure successful deployment of models into production environments, focusing on stability, reliability, and seamless integration
• Continuously track the performance of AI/ML solutions in production, addressing any issues, identifying model drift, and making necessary optimizations
• Manage and automate model evaluation, training, and deployment processes using cloud infrastructure, with a focus on GCP (experience with AWS or Azure is also acceptable)
• Fine-tune machine learning models to maximize performance and scalability, ensuring they meet diverse and evolving user needs
• Understand both company and customer challenges, leveraging AI capabilities to develop innovative solutions that address these problems
• Ensure the development and deployment of scalable, efficient, and high-quality AI solutions that meet business needs
• Participate in design, architecture, and code reviews. Foster collaboration within the team, ensuring high-quality code standards are maintained while guiding the team through technical challenges and roadmap deliverables
• Design and build efficient, resilient machine learning platforms and software products capable of scaling to meet production demands
• Adhere to best practices for data privacy and security, ensuring full compliance when working with sensitive data
• Actively seek opportunities to enhance and upgrade AI/ML infrastructure, tools, and solutions
• Improve best practices for machine learning engineering by producing high-quality code, documentation, automated tests, and precise monitoring systems

Preferred Qualifications

• Experience working in distributed systems-based architectures, developing APIs, and implementing/deploying scalable backend services
• Hands-on experience in data engineering, orchestration, ETL, and distributed unstructured data processing
• Experience with cloud infrastructure, including Docker/Kubernetes deployments, security, and cost optimization
• Knowledge of healthcare standards such as HL7, FHIR, or HIPAA compliance

Benefits

• Flexible work hours; fully remote team
• Paid parental leave for biological and adopted children
• Half-day Fridays, every Friday
• 18 paid company holidays, including a one week mid-year and one week end-of-year break
• 9 wellness days to be used for self-care- or anything that comes up in life
• 15 days of PTO
• 1-month (20 working days) paid sabbatical after the 4-year anniversary, and every 4 years thereafter
• Generous medical, dental, and vision insurance for employees and their families
• Health Savings Accounts and Flexible Spending Accounts
• 401k retirement plan
• Short & long-term disability insurance
• $100 per employee yearly wellness budget, with flexibility to spend on physical, emotional, and mental wellness resources
• PerkSpot: Instant access to discounts on products & services from hundreds of vendors
• Annual budget for professional and personal development (webinars, online courses, books, and more)