AI Engineer

4 weeks ago

Paul, United States Yeah! Global Full time

This is a remote position.

Note: One of our clients is building a new team and hiring 8 AI Engineers globally. This is a 100% remote role. This role does not offer any visa sponsorship.


Job Summary:

As an AI Engineer you will be responsible for designing developing and implementing AI models and algorithms that solve complex business problems. You will work closely with data scientists software engineers and product teams to integrate AI solutions into our products. Your role will involve researching the latest AI technologies building scalable machine learning models and optimizing algorithms for performance and accuracy.


Key Responsibilities:

  • Design develop and deploy AI models and algorithms that address business needs and challenges.
  • Collaborate with data scientists and software engineers to collect preprocess and yze large datasets.
  • Implement machine learning and deep learning models using frameworks like TensorFlow PyTorch or Keras.
  • Optimize and tune models for performance accuracy and scalability.
  • Integrate AI solutions into production systems ensuring seamless operation and reliability.
  • Research and stay uptodate with the latest advancements in AI machine learning and data science.
  • Develop and maintain doentation for AI models processes and best practices.
  • Participate in code reviews and provide feedback to ensure highquality code and adherence to best practices.
  • Trouble and resolve issues related to AI models and systems in production environments.
  • Collaborate with crossfunctional teams to ensure AI solutions align with business goals and objectives.


Qualifications:

  • Bachelor s degree in Computer Science Engineering Mathematics or a related field.
  • 3 years of experience in AI machine learning or a related field.
  • Proficiency in programming languages such as Python R or Java.
  • Experience with machine learning frameworks like TensorFlow PyTorch Keras or Scikitlearn.
  • Strong understanding of machine learning algorithms neural networks natural language processing (NLP) and computer vision.
  • Experience with data preprocessing feature engineering and model evaluation techniques.
  • Familiarity with cloud platforms and tools for AI and machine learning (e.g. AWS Google Cloud Azure).
  • Strong problemsolving ss and ability to work with complex datasets.
  • Excellent communication and collaboration ss with the ability to work effectively in a team environment.
  • Ability to manage multiple projects and deliver results on time.


Preferred Qualifications:

  • Master s or PhD in Computer Science AI Machine Learning or a related field.
  • Experience with big data technologies such as Hadoop Spark or Kafka.
  • Knowledge of reinforcement learning generative models or advanced neural architectures.
  • Familiarity with DevOps practices for AI/ML including CI/CD pipelines and containerization.
  • Relevant certifications in AI or machine learning.


Bachelor s degree in Computer Science, Engineering, Mathematics, or a related field. 3+ years of experience in AI, machine learning, or a related field. Proficiency in programming languages such as Python, R, or Java. Experience with machine learning frameworks like TensorFlow, PyTorch, Keras, or Scikit-learn. Strong understanding of machine learning algorithms, neural networks, natural language processing (NLP), and computer vision. Experience with data preprocessing, feature engineering, and model evaluation techniques. Familiarity with cloud platforms and tools for AI and machine learning (e.g., AWS, Google Cloud, Azure). Strong problem-solving ss and ability to work with complex datasets. Excellent communication and collaboration ss, with the ability to work effectively in a team environment. Ability to manage multiple projects and deliver results on time. Preferred Qualifications: Master s or PhD in Computer Science, AI, Machine Learning, or a related field. Experience with big data technologies such as Hadoop, Spark, or Kafka. Knowledge of reinforcement learning, generative models, or advanced neural architectures. Familiarity with DevOps practices for AI/ML, including CI/CD pipelines and containerization. Relevant certifications in AI or machine learning.

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