AI/ML Engineer

Robotics Technologies LLC
Albany, NY, United States
4 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Compensation
$151,840
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Software Applications Artificial Neural Networks Microsoft Azure Big Data Software Code Optimization Computer Programming Continuous Integration Data Cleansing R (Programming Language) Python (Programming Language)
+29 more
Machine Learning Natural Language Processing NumPy Tensorflow Azure Machine Learning Sentiment Analysis Software Engineering SQL Databases Data Processing Enterprise Software Applications Feature Engineering Pytorch Large Language Models Google Vertex AI Deep Learning Model Validation Generative AI Git Pandas Matplotlib Build Management Scikit Learn Machine Learning Operations Restful APIs Document Classification Docker Unsupervised Learning Jenkins Microservices

Job description

We are seeking an experienced AI/ML Engineer to design, develop, and deploy artificial intelligence and machine learning solutions. The ideal candidate should have strong programming skills, experience with machine learning algorithms, deep learning, data processing, and model deployment., * Design, develop, and implement machine learning models and AI solutions.

  • Build predictive models using supervised and unsupervised learning techniques.
  • Develop AI-powered applications using Python and machine learning frameworks.
  • Work with large datasets to perform data preprocessing, feature engineering, and model training.
  • Implement deep learning models using TensorFlow and PyTorch.
  • Develop Natural Language Processing (NLP) solutions for text classification and sentiment analysis.
  • Build and deploy generative AI and Large Language Model (LLM) applications.
  • Develop and optimize neural networks and predictive algorithms.
  • Integrate AI/ML models with REST APIs and enterprise applications.
  • Perform model evaluation, validation, and hyperparameter tuning.
  • Deploy machine learning models using cloud platforms such as AWS, Azure, or GCP.
  • Collaborate with data scientists, data engineers, and software development teams.
  • Monitor model performance and improve accuracy and scalability.

Requirements

  • Python, SQL, and R.
  • Machine Learning and Deep Learning.
  • TensorFlow, PyTorch, and Scikit-learn.
  • Natural Language Processing (NLP).
  • Generative AI and Large Language Models (LLMs).
  • Neural Networks and Predictive Analytics.
  • Pandas, NumPy, and Matplotlib.
  • Feature Engineering and Model Optimization.
  • REST APIs and Microservices.
  • Docker and Kubernetes.
  • AWS SageMaker, Azure ML, or Google Vertex AI.
  • Git, Jenkins, and CI/CD pipelines.

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