Machine Learning Engineer

RESPONSIBILITIES

Kforce has a client in San Jose, CA that is seeking a hands-on Machine Learning Engineer to help build and operationalize ML capabilities supporting a learning opportunity-assessment solution. This role will translate ML and analytical strategies into repeatable feature pipelines, ML workflows, model lifecycle processes, and data integrations.

Key Responsibilities

• Build and maintain feature-engineering and ML pipelines
• Develop repeatable workflows for data preprocessing, model training, evaluation, inference, and retraining
• Operationalize ML models beyond experimentation into scalable execution processes
• Implement model versioning, experiment tracking, monitoring, testing, and reproducibility practices
• Develop data ingestion and integration workflows across enterprise environments
• Partner closely with Data Scientists and technical stakeholders to move ML solutions from concept to implementation

REQUIREMENTS:

• Strong hands-on Python and SQL development
• Experience building ML and feature-engineering pipelines, beyond traditional ETL/data engineering
• Experience with Scikit-learn or comparable ML frameworks
• Strong understanding of features, model training, evaluation, inference, and operationalization
• Experience with structured and unstructured data processing using Pandas, NumPy, or similar libraries
• Experience with model registries, versioning, experiment tracking, monitoring, automated testing, and retraining workflows
• Experience with cloud-based ML/data environments, APIs, integrations, and version-control practices
• Strong software engineering fundamentals and experience developing production-oriented ML solutions

Preferred Skills

• MLflow or similar lifecycle tooling, Feature Stores, containerization, cloud ML platforms, NLP/text-processing pipelines, automated ML testing, enterprise data platforms, and large-scale enterprise ML experience
• Ideal Profile: A hands-on ML engineer who has successfully moved models beyond notebooks into reliable, repeatable, operational ML workflows

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
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.

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