Machine Learning Engineer / Data Scientist
Budget / Salary$100,700–167,800
TypeFull-time job
LocationUnited States
Posted1 hour ago
This is a remote role; however, we only operate in the following states: AZ, CA, CO, FL, GA, IL, IN, MA, MI, MN, MO, NJ, NY, NC, OH, PA, TX and WI.
ABOUT US AND ABOUT YOU
Clinician Nexus enables health care organizations to build thriving clinician teams with industry-leading technology products, workforce and compensation analytics, and automated workflow solutions. Backed by extensive technical expertise and industry-leading data, we deliver innovative approaches to help clients plan, educate, and engage their clinical workforce at every stage of the lifecycle. We are committed to providing our clients with outstanding guidance and support as they work to shape the future of health care.
JOB SUMMARY
We are seeking a highly skilled and motivated Machine Learning Engineer to join our growing Data Science team. You will develop and deploy cutting-edge machine learning models and advanced data analytics solutions to solve real-world problems. You will collaborate with cross-functional teams (Product, Data Platform, DevOps, Software Engineering, etc.) to extract meaningful insights from data, develop scalable machine learning solutions, and help drive data-informed decision-making.
PRIMARY ACCOUNTABILITIES
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
KNOWLEDGE, SKILLS AND ABILITIES
Minimum Required Qualifications
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.
Behavioral
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
Preferred Qualifications
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
SALARY, BENEFITS AND PERKS
Competitive total compensation package
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
Additional perks
WORK ENVIRONMENT
Reflected below is the base salary range offered for this position. Actual salaries may vary depending on factors including but not limited to academic achievements, skills and experience. The range listed is just one component of the compensation package offered to candidates.
$100,700 - $167,800
Our Values in Action: How We CARE
We live our values daily through four commitments:
Connect:Collaborate selflessly to support others, advance ideas, and solve problems using critical thinking.
Act:Bring integrity and respect to every interaction—no exceptions.
Reach:Commit to continuous learning and knowledge sharing that strengthens teams and clients.
Embrace:Foster inclusion and belonging so everyone can thrive and contribute.
SullivanCotter Holdings (Clinician Nexus, SCH Services, SullivanCotter) is an Equal Employment Opportunity/Affirmative Action employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status, sexual orientation, gender identity or expression, marital status, genetic information, or any other characteristic protected by law or marital status.
Originally posted on Himalayas
ABOUT US AND ABOUT YOU
Clinician Nexus enables health care organizations to build thriving clinician teams with industry-leading technology products, workforce and compensation analytics, and automated workflow solutions. Backed by extensive technical expertise and industry-leading data, we deliver innovative approaches to help clients plan, educate, and engage their clinical workforce at every stage of the lifecycle. We are committed to providing our clients with outstanding guidance and support as they work to shape the future of health care.
JOB SUMMARY
We are seeking a highly skilled and motivated Machine Learning Engineer to join our growing Data Science team. You will develop and deploy cutting-edge machine learning models and advanced data analytics solutions to solve real-world problems. You will collaborate with cross-functional teams (Product, Data Platform, DevOps, Software Engineering, etc.) to extract meaningful insights from data, develop scalable machine learning solutions, and help drive data-informed decision-making.
PRIMARY ACCOUNTABILITIES
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
KNOWLEDGE, SKILLS AND ABILITIES
Minimum Required Qualifications
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.
Behavioral
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
Preferred Qualifications
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
SALARY, BENEFITS AND PERKS
Competitive total compensation package
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
Additional perks
WORK ENVIRONMENT
Reflected below is the base salary range offered for this position. Actual salaries may vary depending on factors including but not limited to academic achievements, skills and experience. The range listed is just one component of the compensation package offered to candidates.
$100,700 - $167,800
Our Values in Action: How We CARE
We live our values daily through four commitments:
Connect:Collaborate selflessly to support others, advance ideas, and solve problems using critical thinking.
Act:Bring integrity and respect to every interaction—no exceptions.
Reach:Commit to continuous learning and knowledge sharing that strengthens teams and clients.
Embrace:Foster inclusion and belonging so everyone can thrive and contribute.
SullivanCotter Holdings (Clinician Nexus, SCH Services, SullivanCotter) is an Equal Employment Opportunity/Affirmative Action employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status, sexual orientation, gender identity or expression, marital status, genetic information, or any other characteristic protected by law or marital status.
Originally posted on Himalayas
Apply on Himalayas →
Job sourced from Himalayas. Applications happen directly on the original platform — we never collect your data.