Machine Learning Engineer / AI Engineer

Machine Learning Engineer / AI Engineer
Newark, NJ
Salary: $120,000 – $180,000

Description / Position Overview

This role owns the design, deployment, and long-term performance of production machine learning systems that power data-driven products and operational intelligence.

The Machine Learning Engineer is responsible for translating business problems into scalable AI solutions. This includes building end-to-end pipelines, deploying models into production environments, and continuously improving model performance.

This is an engineering execution role, not a research-only position. Success requires the ability to move models from experimentation to reliable production systems that drive measurable product and operational impact.

Requirements

• Experience building and deploying machine learning models in real-world production environments
• Strong Python programming capability and experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn
• Understanding of statistics, probability, and optimization techniques used in machine learning systems
• Experience working with large-scale structured and unstructured datasets
• Experience deploying and operating models on cloud platforms such as AWS, GCP, or Azure
• Ability to build and manage scalable data pipelines supporting ML workflows
• Strong collaboration skills working with product, engineering, and data teams

Responsibilities

Machine Learning Development

• Design, train, and optimize machine learning models for real-world business applications
• Build end-to-end ML pipelines including data ingestion, preprocessing, training, and evaluation
• Select appropriate algorithms and modeling approaches based on problem context
• Continuously improve model performance through experimentation and iteration

Production Deployment & Infrastructure

• Deploy machine learning models into scalable production environments
• Build APIs and services that operationalize machine learning capabilities inside products and systems
• Manage the full model lifecycle including monitoring, retraining, and drift detection
• Ensure reliability, scalability, and maintainability of ML infrastructure

Data & Engineering Execution

• Work with structured and unstructured data sources to support model development
• Implement feature engineering strategies that improve model accuracy and reliability
• Collaborate with data engineering teams to maintain clean and scalable data infrastructure
• Optimize model performance and resource efficiency in production systems

Cross-Functional Collaboration

• Partner with product and engineering teams to translate business needs into machine learning solutions
• Communicate technical insights and model behavior to non-technical stakeholders
• Contribute to AI roadmap planning and prioritization of ML initiatives

Must-Haves

• Proven experience deploying machine learning models into production environments
• Strong Python and ML framework expertise (TensorFlow, PyTorch, or Scikit-learn)
• Experience building scalable ML pipelines and APIs
• Experience working with cloud infrastructure (AWS, GCP, or Azure)
• Strong understanding of statistical modeling and machine learning fundamentals

Final Invitation to Apply

If you are a hands-on machine learning engineer who thrives on building real-world AI systems and taking models from concept to production impact, this is an opportunity to own meaningful technology that drives product innovation and operational performance.

Contact

Email Resume: [email protected]

Apply Online:

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