AI/ML Engineer

Job Overview:

We are looking for a talented and driven AI/ML Engineer to join our team in Newark, NJ. In this role, you will design, build, and deploy machine learning models and AI solutions that solve complex business problems. You’ll work closely with data scientists, software engineers, and product teams to bring intelligent features and automation into our systems and services.

Key Responsibilities:

Design and develop machine learning models for classification, regression, clustering, NLP, or computer vision tasks.

Build end-to-end ML pipelines, from data preprocessing and model training to deployment and monitoring.

Evaluate model performance, fine-tune hyperparameters, and retrain models based on changing data.

Implement scalable AI solutions using cloud platforms (AWS, Azure, GCP) and ML frameworks (TensorFlow, PyTorch, scikit-learn).

Collaborate with data engineers to optimize data pipelines and ensure clean, reliable datasets.

Integrate ML models into production systems via APIs or edge deployments.

Stay current with the latest AI/ML research, technologies, and best practices.

Contribute to model governance, documentation, and explainability standards.

Required Skills and Qualifications:

3+ years of experience in applied machine learning or AI engineering.

Proficiency in Python and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost).

Strong understanding of algorithms in supervised and unsupervised learning.

Experience building and deploying ML models in production environments.

Familiarity with data processing frameworks (Pandas, NumPy, Spark) and version control (Git).

Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Airflow, SageMaker).

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.

Preferred Qualifications:

Experience with NLP, computer vision, or generative AI (e.g., GPT, LLaMA, BERT).

Hands-on experience with containerization (Docker, Kubernetes).

Familiarity with cloud-based AI services (e.g., AWS SageMaker, Azure ML, Google Vertex AI).

Knowledge of data privacy and responsible AI principles.