Senior AI/ML Engineer

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CareMessage

πŸ’΅ $189k
πŸ“Remote - United States

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)
This job is filled or no longer available