Senior AI/ML Engineer - Remote Contract-to-Hire: 6 months, then convert to FTE Pay Rate: $80 - $90/hr 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. Nice to Have: • 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. Job Responsibilities Model Design & Development: • 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 Infrastructure, Scaling & Deployment: • 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. Problem-Solving & Business Impact: • 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. Technical Expertise & Architecture: • 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. Desired Skills and Experience Engineering, AI / ML, Data Science, ETL, Python, NLP, Generative AI, LLMs, MLOps, Cloud All qualified applicants will receive consideration for employment without regard to race, color, national origin, age, ancestry, religion, sex, sexual orientation, gender identity, gender expression, marital status, disability, medical condition, genetic information, pregnancy, or military or veteran status. We consider all qualified applicants, including those with criminal histories, in a manner consistent with state and local laws, including the California Fair Chance Act, City of Los Angeles' Fair Chance Initiative for Hiring Ordinance, and Los Angeles County Fair Chance Ordinance. For unincorporated Los Angeles county, to the extent our customers require a background check for certain positions, the Company faces a significant risk to its business operations and business reputation unless a review of criminal history is conducted for those specific job positions.