Skale
This range is provided by Skale. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range $180,000.00/yr - $220,000.00/yr
Principal Recruiter – Building ML and engineering teams in the US We’re working with a Series A health tech start-up pioneering a revolutionary approach to healthcare AI, developing neurosymbolic systems that combine statistical learning with structured medical knowledge. Their technology is being adopted by leading health systems and insurers to enhance patient outcomes through advanced predictive analytics.
We’re seeking Machine Learning Engineers who excel at the intersection of data science, modeling, and software engineering. You'll design and implement models that extract insights from longitudinal healthcare data, balancing analytical rigor, interpretability, and scalability.
This role offers a unique opportunity to tackle foundational modeling challenges in healthcare, where your contributions will directly influence clinical, actuarial, and policy decisions.
Key Responsibilities
Develop predictive models to forecast disease progression, healthcare utilization, and costs using temporal clinical data (claims, EHR, laboratory results, pharmacy records)
Design interpretable and explainable ML solutions that earn the trust of clinicians, actuaries, and healthcare decision-makers
Research and prototype innovative approaches leveraging both classical and modern machine learning techniques
Build robust, scalable ML pipelines for training, validation, and deployment in distributed computing environments
Collaborate cross‑functionally with data engineers, clinicians, and product teams to ensure models address real‑world healthcare needs
Communicate findings and methodologies effectively through visualizations, documentation, and technical presentations
Required Qualifications
Strong foundation in statistical modeling, machine learning, or data science, with preference for experience in temporal or longitudinal data analysis
Proficiency in Python and ML frameworks (PyTorch, JAX, NumPyro, PyMC, etc.)
Proven track record of transitioning models from research prototypes to production systems
Experience with probabilistic methods, survival analysis, or Bayesian inference (highly valued)
Bonus Qualifications
Experience working with clinical data and healthcare terminologies (ICD, CPT, SNOMED CT, LOINC)
Background in actuarial modeling, claims forecasting, or risk adjustment methodologies
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Information Technology
Industries Staffing and Recruiting
#J-18808-Ljbffr
Base pay range $180,000.00/yr - $220,000.00/yr
Principal Recruiter – Building ML and engineering teams in the US We’re working with a Series A health tech start-up pioneering a revolutionary approach to healthcare AI, developing neurosymbolic systems that combine statistical learning with structured medical knowledge. Their technology is being adopted by leading health systems and insurers to enhance patient outcomes through advanced predictive analytics.
We’re seeking Machine Learning Engineers who excel at the intersection of data science, modeling, and software engineering. You'll design and implement models that extract insights from longitudinal healthcare data, balancing analytical rigor, interpretability, and scalability.
This role offers a unique opportunity to tackle foundational modeling challenges in healthcare, where your contributions will directly influence clinical, actuarial, and policy decisions.
Key Responsibilities
Develop predictive models to forecast disease progression, healthcare utilization, and costs using temporal clinical data (claims, EHR, laboratory results, pharmacy records)
Design interpretable and explainable ML solutions that earn the trust of clinicians, actuaries, and healthcare decision-makers
Research and prototype innovative approaches leveraging both classical and modern machine learning techniques
Build robust, scalable ML pipelines for training, validation, and deployment in distributed computing environments
Collaborate cross‑functionally with data engineers, clinicians, and product teams to ensure models address real‑world healthcare needs
Communicate findings and methodologies effectively through visualizations, documentation, and technical presentations
Required Qualifications
Strong foundation in statistical modeling, machine learning, or data science, with preference for experience in temporal or longitudinal data analysis
Proficiency in Python and ML frameworks (PyTorch, JAX, NumPyro, PyMC, etc.)
Proven track record of transitioning models from research prototypes to production systems
Experience with probabilistic methods, survival analysis, or Bayesian inference (highly valued)
Bonus Qualifications
Experience working with clinical data and healthcare terminologies (ICD, CPT, SNOMED CT, LOINC)
Background in actuarial modeling, claims forecasting, or risk adjustment methodologies
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Information Technology
Industries Staffing and Recruiting
#J-18808-Ljbffr