Machine Learning Engineer – Portfolio Value Creation at VDS Consulting Group

Atlanta, Georgia, United States -

Full Time

Start Date

Immediate

Expiry Date

01 Mar, 26

Salary

0.0

Posted On

01 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Python, TensorFlow, PyTorch, MLOps, Data Engineering, Predictive Maintenance, Demand Forecasting, Pricing Optimization, Anomaly Detection, Data Privacy, Model Explainability, Cloud Platforms, Agile Iteration, Communication Skills, Mentoring

Industry

Business Consulting and Services

Description

Machine Learning Engineer – Portfolio Value Creation As a Contract Machine Learning Engineer within Value Driven Solutions' Agentic AI Practice, you will lead the design, development, and deployment of scalable ML models tailored to accelerate value creation in private equity-backed portfolio companies (portcos) with revenues ranging from $50M to $2B. Reporting directly to portfolio operating executives and PE deal teams, you will embed on-site (up to 75% travel) to identify high-impact use cases—such as predictive maintenance for industrial assets, dynamic demand forecasting for consumer goods, pricing optimization for SaaS platforms, and working capital improvements through anomaly detection—and transform them into production-ready solutions that deliver measurable EBITDA uplift (targeting >$5M annual impact per initiative). Your role will involve conducting data maturity assessments across disparate legacy systems, architecting end-to-end ML pipelines using Python, TensorFlow/PyTorch, and MLOps tools like Kubeflow and MLflow, and ensuring seamless integration with existing ERP/CRM environments (e.g., SAP, Salesforce). You will collaborate with cross-functional teams—including data engineers, domain SMEs, and C-suite stakeholders—to prototype models, validate performance via A/B testing and ROI modeling, and scale deployments across multiple portcos while adhering to governance standards for data privacy (GDPR/CCPA) and model explainability (SHAP/LIME). Success in this role requires a proven track record of shipping ML solutions in high-stakes, resource-constrained environments, such as PE transformations or industrial operations, where you've quantified business outcomes like 15-25% reductions in downtime or 10-20% revenue uplift from optimized pricing. This position demands hands-on expertise in handling unstructured industrial data (IoT sensors, supply chain logs), cloud-based orchestration (AWS SageMaker, Azure ML), and agile iteration to align with 100-day value-creation plans. Ideal candidates thrive in fast-paced, matrixed organizations, bridging technical execution with executive storytelling to secure buy-in for AI adoption. With Value Driven Solutions' white-glove support, you'll gain direct exposure to PE partners and a network of portco leaders, positioning you for long-term engagements or permanent transitions. Key Responsibilities: 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. Required Qualifications: 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. Preferred Experience: Prior work with Ignition SCADA or IIoT integrations in manufacturing/food & beverage sectors. Familiarity with ISA-95 standards for enterprise-system interoperability. Consulting background in digital transformation, with exposure to third-party vendor evaluations. To apply: Send CV + short note on the specific impact you’ve driven with ML in private-equity or industrial settings to info@valuedrivensolutions.com. Include role title in subject line and your availability. Leadership Solutions – Value Driven Solutions Accelerating Agentic AI adoption in private equity portfolios

Responsibilities

Lead the design, development, and deployment of scalable ML models to accelerate value creation in private equity-backed portfolio companies. Conduct data maturity assessments and collaborate with cross-functional teams to prototype models and scale deployments.