Machine Learning Engineer – Portfolio Value Creation
Value Driven Solutions
contract
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
AWSAzureCloudGoogle Cloud PlatformNoSQLPythonPyTorchScikit-LearnSQLTableauTensorflow
About the role
- Lead ML maturity assessments and co-develop 12-24 month AI roadmaps aligned with portfolio theses (e.g., operational efficiency, revenue growth)
- Build and optimize supervised/unsupervised models for core use cases, ensuring >90% accuracy and low-latency inference for real-time applications
- Drive MLOps best practices: CI/CD pipelines, model monitoring/drift detection, and federated learning for multi-portco data silos
- Quantify and report impact via dashboards (Tableau/Power BI), presenting to boards on metrics like NPV, IRR, and payback periods
- Mentor junior engineers and facilitate knowledge transfer to portco teams for sustained post-contract ownership
Requirements
- Bachelor's/ Master's in computer science, Data Science, or related field (PhD preferred for advanced modeling)
- 5+ years in ML engineering, with 2+ years in PE/industrial contexts delivering >$5M quantified value
- Proficiency in Python/R, scikit-learn, TensorFlow/PyTorch, SQL/NoSQL, and cloud platforms (AWS/GCP/Azure)
- Experience with edge ML (e.g., TensorFlow Lite) and ethical AI (bias mitigation, fairness audits)
- Strong communication skills for translating complex models into executive summaries and workshops
Benefits
- white-glove support
- direct exposure to PE partners
- network of portco leaders
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learning engineeringsupervised modelsunsupervised modelsMLOpsCI/CD pipelinesmodel monitoringdrift detectionfederated learningPythonR
Soft skills
mentoringcommunicationknowledge transferpresentation skills
Certifications
Bachelor's degreeMaster's degreePhD