Machine Learning Engineer Quantization Jobs in Mount Royal, NJ

JOB SUMMARY
We are seeking a hands-on Machine Learning Engineer to design, build, evaluate, deploy, and maintain machine learning models in production environments. The ideal candidate will have strong expertise in Python, PySpark, AWS, and machine learning model development, with a proven track record of delivering production-ready models that drive business outcomes. This role requires a highly technical individual contributor who can analyze data, compare model performance, optimize solutions, and manage the complete machine learning lifecycle. Experience with local LLM deployments is required, but the primary focus of this role is traditional machine learning model development and production deployment.
KEY RESPONSIBILITIES
• Design, develop, train, test, and deploy machine learning models for enterprise-scale business applications.
• Analyze new and existing datasets to evaluate opportunities for model improvements and enhanced predictive performance.
• Build, compare, and validate multiple machine learning models to determine the most effective production solution.
• Perform feature engineering, model selection, hyperparameter tuning, and model optimization.
• Develop scalable data processing pipelines using Python and PySpark.
• Deploy, monitor, maintain, and improve machine learning models in production environments.
• Assess model performance using appropriate statistical methods and machine learning evaluation metrics.
• Collaborate with business stakeholders and technical teams to identify opportunities for machine learning solutions.
• Conduct exploratory data analysis and provide insights to support data-driven decision-making.
• Work with large-scale datasets within AWS cloud environments.
• Develop reproducible machine learning workflows and maintain technical documentation.
• Troubleshoot production model issues and implement continuous improvements.
• Support experimentation and proof-of-concept initiatives related to machine learning and AI technologies.
• Configure and manage local LLM environments where required to support business use cases.
• Participate in technical discussions, code reviews, and best practice initiatives.
REQUIRED QUALIFICATIONS
• Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related field.
• Minimum 5 years of experience as a Machine Learning Engineer.
• Strong hands-on programming expertise in Python.
• Recent and relevant experience using PySpark for large-scale data processing and machine learning workflows.
• Proven experience developing, training, evaluating, and deploying machine learning models into production environments.
• Experience comparing multiple machine learning algorithms to determine the best-performing production solution.
• Strong understanding of machine learning concepts, including:
- Classification
- Regression
- Clustering
- Ensemble Methods
- Random Forest
- Gradient Boosting
- Feature Engineering
- Model Evaluation
• Experience working with AWS cloud services and machine learning infrastructure.
• Strong data analysis and statistical modeling skills.
• Experience monitoring, maintaining, and improving production machine learning models.
• Experience working with large and complex datasets.
• Knowledge of machine learning lifecycle management and model governance.
• Experience setting up and managing local Large Language Models (LLMs).
• Strong debugging, analytical, and problem-solving skills.
• Ability to independently manage projects and deliver technical solutions.
• Excellent communication and collaboration skills.
PREFERRED QUALIFICATIONS
• Experience with MLOps tools and model monitoring frameworks.
• Experience with machine learning experimentation platforms.
• Familiarity with distributed computing and big data technologies.
• Experience optimizing machine learning workloads in cloud environments.
• Knowledge of advanced machine learning algorithms and predictive analytics techniques.
• Experience within telecommunications, construction workflow management, or enterprise operations environments.
• Exposure to Generative AI technologies in addition to traditional machine learning solutions.
CERTIFICATIONS
• AWS Certified Machine Learning - Specialty (Preferred)
• AWS Certified Solutions Architect - Associate or Professional (Preferred)
• Databricks Machine Learning Certification (Preferred)
• Google Professional Machine Learning Engineer (Preferred)
• Relevant Python, Data Science, or Machine Learning Certifications (Preferred)