[Remote] Machine Learning Engineer / Data Scientist

Note: The job is a remote job and is open to candidates in USA. Clinician Nexus is a company that enables health care organizations to build thriving clinician teams with innovative technology products. They are seeking a highly skilled Machine Learning Engineer to develop and deploy machine learning models and advanced data analytics solutions, collaborating with cross-functional teams to drive data-informed decision-making. Responsibilities • Design, develop, and deploy ML solutions ranging from traditional ML applications (classification, clustering, recommendations) to LLM-based systems, including document parsing, data extraction, RAG pipelines, and LLM agents • Write clean, maintainable, production-quality Python code that integrates smoothly with existing engineering and deployment infrastructure • Work with large datasets to clean, preprocess, and analyze data, ensuring data quality and integrity • Implement and optimize algorithms using best practices in machine learning, deep learning, and statistical analysis • Collaborate with business stakeholders to understand requirements and deliver data-driven solutions that provide actionable insights • Develop and maintain scalable pipelines and infrastructure for data processing and model training, versioning, deployment, and monitoring • Evaluate the performance of machine learning models, including LLM-specific evaluation approaches, and tune models for optimal performance • Communicate findings, insights, and model performance to both technical and non-technical audiences • Continuously stay updated on the latest trends, technologies, and best practices Skills • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. or related experience • Bachelor with 5+ years of relevant experience • Master or higher with 3+ years of relevant experience • Fluent in Python (3+ years of coding experience) • Strong software development practices in Python, including writing maintainable, testable, production-ready code • Solid understanding of LLM architectures and Generative AI • Hands-on experience building and evaluating RAG pipelines • Experience with LLM orchestration frameworks (LangChain, LlamaIndex, or similar) • Proficiency in machine learning libraries such as Scikit-learn and PyTorch; and fundamental libraries such as NumPy and Pandas • Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and containerization tools (e.g., Docker) • Strong understanding of model evaluation metrics across traditional ML (e.g., accuracy, precision, recall, F1) and LLM-based systems (e.g., faithfulness, answer relevancy, hallucination detection), including approaches for evaluating non-deterministic outputs • Experience with model management tools such as MLFlow and the model development life cycle • Experience with version control tools such as Git • Proficiency in adapting SDLC best practices for code development and testing • Excellent problem-solving skills, analytical thinking, and the ability to work in a fast-paced environment • Strong communication skills and the ability to explain complex technical concepts to non-technical stakeholders • Collaborator: work effectively with others, including domain experts, engineers, and business stakeholders • Inquisitive: desire to ask questions and get a deeper understanding of issues • Innovative: ability to imagine new analytical solutions to any problem • Confident: able to challenge perceptions and biases of individuals at every level of the organization • Curious: stays abreast of current and upcoming technologies and tools • Business-oriented: solid understanding of business requirements and vernacular • Familiarity with optimizing, deploying and scaling automated training pipelines of transformer-based models • Familiarity with distributed training techniques and GPU-accelerated computing • Familiarity with classical NLP approaches • Experience implementing CI/CD pipelines for ML models for automating training, validation, monitoring, and scalable deployment • Experience with integrating and deploying AWS AI/ML services • Experience with Databricks • Experience in Health Care data Benefits • Medical and dental coverage at no premium cost for employees • 401(k) and profit-sharing retirement plans • Flexible spending accounts • Paid time off (PTO) • Company-paid holidays • Gender-neutral parental leave • Bereavement and pet leave • Continuing education and professional accreditation sponsorship • Life and AD&D insurance • Short- and long-term disability • Employee assistance program • Mental health support program •