AI/ML Engineer

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Raas Infotek LLC
Charlotte, NC, United States (Remote)
  • Production
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Job Title: Senior AI/ML Engineer

Location: Charlotte, NC (Hybrid)

Employment Type: W2 Only (NO C2C/1099)

Duration: 12 Months

About the Role:

We are seeking a highly skilled Senior AI/ML Engineer to lead the design, development, and deployment of advanced machine learning and artificial intelligence solutions. This role is ideal for someone who thrives in a fast-paced, data-driven environment and is passionate about solving complex problems using cutting-edge AI/ML technologies.

Key Responsibilities:

  • Design, develop, and deploy machine learning models , deep learning architectures , and AI-driven applications.
  • Collaborate with data scientists, data engineers, and product teams to translate business requirements into scalable ML solutions.
  • Build and optimize end-to-end ML pipelines for data ingestion, feature engineering, model training, evaluation, and deployment.
  • Leverage cloud platforms such as AWS , Azure , or Google Cloud Platform for scalable model training and deployment.
  • Apply MLOps best practices to automate model versioning, testing, monitoring, and retraining.
  • Conduct exploratory data analysis (EDA) and use statistical techniques to extract insights from large datasets.
  • Work with structured and unstructured data, including text, images, and time-series data.
  • Stay current with the latest research and trends in AI/ML and apply them to real-world problems.
  • Mentor junior engineers and contribute to the development of internal AI/ML frameworks and tools.

Required Skills & Qualifications:

  • 10 years of experience in machine learning , data science , or AI engineering roles.
  • Strong programming skills in Python and experience with libraries such as TensorFlow , PyTorch , scikit-learn , XGBoost , and Pandas.
  • Experience with deep learning , NLP , computer vision , or time-series forecasting.
  • Proficiency in SQL and working with large-scale datasets.
  • Hands-on experience with cloud platforms (AWS/Google Cloud Platform/Azure) and ML services (e.g., SageMaker, Vertex AI, Azure ML).
  • Familiarity with MLOps tools such as MLflow , Kubeflow , Airflow , or DVC.
  • Strong understanding of data structures , algorithms , and software engineering principles.
  • Excellent problem-solving, communication, and collaboration skills.

Nice to Have:

  • Experience with generative AI , LLMs , or foundation models.
  • Knowledge of big data technologies (e.g., Spark, Hadoop, Kafka).
  • Exposure to data labeling , model explainability , and bias mitigation techniques.
  • Experience with containerization and orchestration tools like Docker and Kubernetes.
  • Publications or contributions to open-source AI/ML projects.

Certifications (Preferred):

  • Google Professional Machine Learning Engineer
  • AWS Certified Machine Learning Specialty
  • Microsoft Certified: Azure AI Engineer Associate
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