Altea Healthcare
Overview
ALTEA Healthcare is a leading healthcare organization committed to revolutionizing the delivery of outpatient/post-acute care. We are seeking a mid-level and a senior or lead-level Machine Learning Engineer to join our team. The ideal candidate will have a strong background in developing and deploying scalable GenAI solutions. As an important member of the AI team, this person will contribute significantly to designing, implementing, and deploying various AI/ML product features to improve care delivery and quality for post-acute patients. Job Title and Details
Job Title:
Senior Machine Learning Engineer, GenAI Location:
On-Site, Houston, TX Employment Type:
Full-Time Compensation:
$150,000-$190,000 USD Responsibilities
Develop and deploy production-ready AI/ML models, with a focus on scalability and monitoring across a broad range of applications within healthcare Write efficient, maintainable, and scalable Python code Collaborate with machine learning scientists, data engineers, front end, back-end developers to write production-ready code Set up and maintain end-to-end pipelines including data ingress, egress, model inference, and model retraining Design, implement, and maintain production-grade FastAPI services to serve and integrate ML models securely and at scale. Incorporate feedback from cross-functional teams and refine the ML-driven applications through quick iteration cycles Maintain best software engineering and MLOps practices within the healthcare industry Document the system architecture, design decisions, and codebase to facilitate future maintenance and enhancements Senior/Lead – Additional Responsibilities
Technical leadership: provide mastery for challenging problems and guide system design and process flow Best practices: create, maintain, and advocate for best practices via documentation Ownership – Enable others: unblock blockers, educate and elevate team members Ability to translate clinical and business requirements into technical specifications, collaborating with clinicians and product stakeholders Key Responsibilities and Qualifications
Proven experience in deploying, scaling, integrating, and maintaining generative AI applications Strong understanding and experience in software engineering and MLOps best practices Experience with unit testing and regression testing to ensure quality and stability Preferred: Experience working with Azure DevOps, Azure App Services, and Azure Functions Preferred: Experience with fine-tuning and pre-training language models and embedding models Preferred: Experience architecting large-scale ML systems integrated with enterprise healthcare data sources (EHRs, clinical workflows, APIs) Preferred: Experience designing and maintaining evaluation frameworks, including dataset drift detection, error analysis, and healthcare-specific metrics to ensure model reliability and safety Note:
This role is specifically focused on the deployment and integration of generative AI applications. It is not intended for data scientists, individuals primarily focused on building dashboards, or those with experience limited to traditional ML models and model development Other Requirements
Bachelor’s or Master’s degree in Engineering, Computer Science, or equivalent experience MS and 5+ years of experience or a PhD with 3+ years are preferred. However, we remain flexible for individuals with demonstrated strong ownership and adaptability in start-up or high growth environments Experience with RAG and multi-agent systems Experience writing production-ready code, troubleshooting and bug fixing Strong proficiency in LangChain, vectorDB and cloud platforms (Azure) Experience with MLOps, monitoring, and CI/CD Experience with transformer-based models, NLP, LLM models, preferably for biomedical/healthcare applications Strong interest in healthcare, with preferred experience working with healthcare data Ability to work independently and collaboratively, manage priorities, and deliver high-quality results within project timelines Self-starter and growth mindset For the senior/lead level: experience leading projects from concept to deployment Benefits
Pay: Competitive pay, benefits, and extremely valuable startup stock options
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ALTEA Healthcare is a leading healthcare organization committed to revolutionizing the delivery of outpatient/post-acute care. We are seeking a mid-level and a senior or lead-level Machine Learning Engineer to join our team. The ideal candidate will have a strong background in developing and deploying scalable GenAI solutions. As an important member of the AI team, this person will contribute significantly to designing, implementing, and deploying various AI/ML product features to improve care delivery and quality for post-acute patients. Job Title and Details
Job Title:
Senior Machine Learning Engineer, GenAI Location:
On-Site, Houston, TX Employment Type:
Full-Time Compensation:
$150,000-$190,000 USD Responsibilities
Develop and deploy production-ready AI/ML models, with a focus on scalability and monitoring across a broad range of applications within healthcare Write efficient, maintainable, and scalable Python code Collaborate with machine learning scientists, data engineers, front end, back-end developers to write production-ready code Set up and maintain end-to-end pipelines including data ingress, egress, model inference, and model retraining Design, implement, and maintain production-grade FastAPI services to serve and integrate ML models securely and at scale. Incorporate feedback from cross-functional teams and refine the ML-driven applications through quick iteration cycles Maintain best software engineering and MLOps practices within the healthcare industry Document the system architecture, design decisions, and codebase to facilitate future maintenance and enhancements Senior/Lead – Additional Responsibilities
Technical leadership: provide mastery for challenging problems and guide system design and process flow Best practices: create, maintain, and advocate for best practices via documentation Ownership – Enable others: unblock blockers, educate and elevate team members Ability to translate clinical and business requirements into technical specifications, collaborating with clinicians and product stakeholders Key Responsibilities and Qualifications
Proven experience in deploying, scaling, integrating, and maintaining generative AI applications Strong understanding and experience in software engineering and MLOps best practices Experience with unit testing and regression testing to ensure quality and stability Preferred: Experience working with Azure DevOps, Azure App Services, and Azure Functions Preferred: Experience with fine-tuning and pre-training language models and embedding models Preferred: Experience architecting large-scale ML systems integrated with enterprise healthcare data sources (EHRs, clinical workflows, APIs) Preferred: Experience designing and maintaining evaluation frameworks, including dataset drift detection, error analysis, and healthcare-specific metrics to ensure model reliability and safety Note:
This role is specifically focused on the deployment and integration of generative AI applications. It is not intended for data scientists, individuals primarily focused on building dashboards, or those with experience limited to traditional ML models and model development Other Requirements
Bachelor’s or Master’s degree in Engineering, Computer Science, or equivalent experience MS and 5+ years of experience or a PhD with 3+ years are preferred. However, we remain flexible for individuals with demonstrated strong ownership and adaptability in start-up or high growth environments Experience with RAG and multi-agent systems Experience writing production-ready code, troubleshooting and bug fixing Strong proficiency in LangChain, vectorDB and cloud platforms (Azure) Experience with MLOps, monitoring, and CI/CD Experience with transformer-based models, NLP, LLM models, preferably for biomedical/healthcare applications Strong interest in healthcare, with preferred experience working with healthcare data Ability to work independently and collaboratively, manage priorities, and deliver high-quality results within project timelines Self-starter and growth mindset For the senior/lead level: experience leading projects from concept to deployment Benefits
Pay: Competitive pay, benefits, and extremely valuable startup stock options
#J-18808-Ljbffr