AI/ML Engineer

PRISTINNO TECHNOLOGY LLC
United States
6 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Software Applications Microsoft Azure Business Software Data Cleansing Data Security Python (Programming Language) Machine Learning Tensorflow Software Engineering Systems Integration
+15 more
Google Cloud Feature Engineering Pytorch LangChain Retrieval-Augmented Generation Large Language Models Model Validation Generative AI Git Scikit Learn Kubernetes Machine Learning Operations Restful APIs Docker Unsupervised Learning

Job description

  • Design, develop, train, and deploy machine learning models for business applications.
  • Build AI-powered solutions using Python and modern machine learning frameworks.
  • Work with structured and unstructured datasets to develop predictive models.
  • Implement and optimize machine learning algorithms for accuracy, scalability, and performance.
  • Collaborate with data engineers, software developers, and business teams to integrate AI/ML solutions.
  • Develop and maintain model pipelines for training, testing, deployment, and monitoring.
  • Explore Generative AI, large language models (LLMs), and retrieval-augmented generation (RAG) solutions.
  • Follow best practices for model evaluation, data security, and responsible AI development.

Requirements

We are looking for an experienced AI/ML Engineer to design, develop, and deploy machine learning solutions and AI-powered applications. The ideal candidate will have strong Python programming skills, hands-on experience with machine learning frameworks, and a solid understanding of AI model development and deployment., * 5+ years of experience in software development, data science, or machine learning.

  • Strong proficiency in Python.
  • Hands-on experience with TensorFlow, PyTorch, or Scikit-learn.
  • Good understanding of supervised and unsupervised learning algorithms.
  • Experience with data preprocessing, feature engineering, and model evaluation.
  • Familiarity with REST APIs and integrating ML models into applications.
  • Experience with Git and collaborative development practices.

Preferred Qualifications

  • Experience with Generative AI, LLMs, LangChain, or RAG.
  • Familiarity with AWS, Microsoft Azure, or Google Cloud Platform.
  • Knowledge of Docker, Kubernetes, or MLflow.
  • Experience deploying and monitoring machine learning models in production.

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