Lead Machine Learning Engineer
Indexed description
- Design, develop, train, and deploy machine learning models and predictive analytics solutions
- Build recommendation engines, customer segmentation models, churn prediction models, and customer value forecasting solutions
- Develop reusable machine learning frameworks, standards, and best practices
- Optimize model performance, scalability, and reliability
- Leverage customer data platforms and identity resolution capabilities to enhance model accuracy
- Create personalized customer experiences and intelligent insights
- Develop solutions that improve customer engagement, retention, and loyalty
- Partner with business stakeholders to align machine learning initiatives with organizational objectives
- Support the development of AI-powered applications and intelligent assistants
- Contribute to Generative AI, LLM, and agent-based AI initiatives
- Evaluate emerging AI technologies and recommend opportunities for adoption
- Collaborate with engineering teams to create innovative AI-enabled business solutions
- Partner with MLOps teams to operationalize machine learning models
- Develop real-time inference and prediction services
- Build model monitoring, validation, retraining, and governance processes
- Ensure secure, scalable, and reliable production deployments
- Provide technical leadership across Machine Learning, Data Science, and Engineering teams
- Mentor engineers and data scientists
- Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or related field required; Master's degree or equivalent advanced experience preferred
- 8+ years of Machine Learning Engineering, Data Science, or Applied AI experience
- 3+ years in a Lead, Principal, or Senior Technical Leadership role
- Experience delivering production-grade machine learning solutions at scale
- Python
- Databricks
- MLflow
- TensorFlow, PyTorch, and/or Scikit-learn
- Real-time inference architectures
- Recommendation systems
- Personalization engines
- Predictive analytics solutions
- Customer intelligence platforms
- Strong understanding of feature engineering and ML lifecycle management
- Experience partnering with Data Engineering teams to build ML-ready data pipelines and datasets
- Customer 360 or customer data platform experience
- Identity Graph experience
- Experience within hospitality, gaming, entertainment, retail, loyalty, or consumer-facing digital organizations
- Snowflake
- MLOps practices and platforms
- Generative AI solutions
- Agentic AI architectures
- LLM-powered applications
- Real-time recommendation platforms
- Experience supporting enterprise AI transformation initiatives
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
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