Machine Learning Developer (Splunk Data Privacy)

Job ID: 35957
Date Added: 11/10/2025
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Job Title: Machine Learning Developer (Splunk data privacy)
Location: Remote (Anywhere in the U.S.)
Position Type: Contractor (Potential conversion to FTE)

Overview:
My client, a leading healthcare organization is seeking an experienced Splunk Privacy and Machine Learning Developer to join its privacy development team. This role focuses on maintaining and enhancing enterprise-scale machine learning models designed to detect inappropriate access to patient records and support privacy compliance. The ideal candidate will have strong development experience in Python, expertise in machine learning modeling, and familiarity with Splunk Enterprise.


Key Responsibilities:
  • Maintain and enhance existing machine learning models for anomaly detection, both supervised and unsupervised.
  • Work in a Unix-based, containerized environment (Red Hat, Podman/Docker) to deploy and optimize ML models.
  • Develop and tune machine learning models using frameworks such as Random Forest, XGBoost, and custom algorithms.
  • Conduct feature engineering, data cleaning, encoding, model validation, and interpretability analyses (SHAP, LIME, feature importance).
  • Collaborate with the technical privacy team to ensure models meet internal compliance and privacy standards.
  • Hit the ground running in a production environment, understanding and supporting existing code and models.
  • Support internal stakeholders with technical expertise; minimal direct customer-facing responsibilities.

Required Skills & Experience:
  • Strong development experience in Python and machine learning modeling in an enterprise environment.
  • Hands-on experience with supervised and unsupervised ML algorithms, anomaly detection, and AI model optimization.
  • Comfortable in Unix/Linux environments and containerized deployments (Podman/Docker).
  • Experience maintaining, tuning, and enhancing existing ML models rather than building from scratch.
  • Familiarity with Splunk Enterprise; certifications are preferred but not required.

Preferred Skills:
  • Splunk Enterprise Security Certified Admin or Splunk Core Certified Consultant credential.
  • Knowledge of Epic Health Connect or other EMR systems.
  • Experience with large-scale production deployments of ML models.

The hourly pay range for this position (dependent on factors including but not limited to client requirements, experience, statutory considerations, and location) is $80-92/hr on W2. Benefits available to full-time employees: medical, dental, vision, disability, life insurance, 401k and commuter benefits.
Synergis is proud to be an Equal Opportunity Employer. We value diversity and do not discriminate on the basis of race, color, ethnicity, national origin, religion, age, gender, gender identity, political affiliation, sexual orientation, marital status, disability, military/veteran status, or any other status protected by applicable law.
Qualified applicants with arrest or conviction records will be considered for employment in accordance with the requirements of applicable state and local laws, including but not limited to, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
For immediate consideration, please forward your resume to (christy.cifreo@synergishr.com).
If you require assistance or an accommodation in the application or employment process, please contact us at (christy.cifreo@synergishr.com).
Synergis is a workforce solutions partner serving thousands of businesses and job seekers nationwide. Our digital world has accelerated the need for businesses to build IT ecosystems that enable growth and innovation along with enhancing the Total Experience (TX). Synergis partners with our clients at the intersection of talent and transformation to scale their balanced teams of tech, digital and creative professionals. Learn more about Synergis at www.synergishr.com.