Machine Learning Engineer

Vortalsoft Inc; New Jersey; On-site; USD 130,000 - 180,000; Full time

Job summary

Vortalsoft Inc. is seeking a Machine Learning Engineer to design, develop, and deploy models that solve complex business problems in a production setting.

The role involves gathering and preprocessing large datasets, selecting algorithms, evaluating performance with standard metrics, and collaborating with data scientists, engineers, and product managers to deliver ML-based solutions.

Qualifications

• Proven ability to design and deploy ML models.

Responsibilities

• Design, develop, and train machine learning models, including supervised, unsupervised, and reinforcement learning algorithms, to solve complex business problems.
• Gather, clean, and preprocess large datasets, ensuring data quality and transforming raw data into formats suitable for machine learning models.
• Analyze the problem domain and select appropriate machine learning algorithms and techniques based on project needs and available data.
• Evaluate model performance using appropriate metrics (e.g., accuracy, precision, recall, AUC) and fine‑tune hyperparameters to optimize performance.
• Deploy machine learning models into production environments, ensuring that models are scalable, efficient, and integrated with existing systems.
• Work closely with cross‑functional teams, including data scientists, software engineers, and product managers, to understand business requirements and deliver machine learning–based solutions.
• Automate repetitive tasks such as data extraction, feature engineering, and model evaluation, and optimize the performance of models in production.
• Stay up-to-date with the latest advancements in machine learning, AI technologies, and industry trends, and incorporate new techniques into existing workflows to improve outcomes.
• Maintain clear documentation on models, experiments, and processes, ensuring that solutions are reproducible and understandable to stakeholders.
• Monitor the performance of deployed models, and update them periodically to reflect changes in data patterns and business requirements.

Job description

Responsibilities

• Design, develop, and train machine learning models, including supervised, unsupervised, and reinforcement learning algorithms, to solve complex business problems.
• Gather, clean, and preprocess large datasets, ensuring data quality and transforming raw data into formats suitable for machine learning models.
• Analyze the problem domain and select appropriate machine learning algorithms and techniques based on project needs and available data.
• Evaluate model performance using appropriate metrics (e.g., accuracy, precision, recall, AUC) and fine‑tune hyperparameters to optimize performance.
• Deploy machine learning models into production environments, ensuring that models are scalable, efficient, and integrated with existing systems.
• Work closely with cross‑functional teams, including data scientists, software engineers, and product managers, to understand business requirements and deliver machine learning–based solutions.
• Automate repetitive tasks such as data extraction, feature engineering, and model evaluation, and optimize the performance of models in production.
• Stay up-to-date with the latest advancements in machine learning, AI technologies, and industry trends, and incorporate new techniques into existing workflows to improve outcomes.
• Maintain clear documentation on models, experiments, and processes, ensuring that solutions are reproducible and understandable to stakeholders.
• Monitor the performance of deployed models, and update them periodically to reflect changes in data patterns and business requirements.