AI Enginee

4 days ago

Bengaluru, India C5i Full time

Role: AI Engineer


1.1 Responsibilities

  1. Design and implement AI models and algorithms to address business challenges and opportunities.
  2. Collaborate with cross-functional teams (including data scientists, software engineers, and product managers) to integrate AI solutions into our products and services.
  3. Conduct data collection, preprocessing, and analysis to ensure the quality and integrity of data used in AI models.
  4. Stay up to date with the latest AI trends, tools, and best practices to continuously improve our AI capabilities.
  5. Evaluate and improve the performance of AI models through rigorous testing and validation.
  6. Document AI development processes, solutions, and results for knowledge sharing and future reference.
  7. Serve as the primary liaison for data labeling, managing communication with in-house teams and third-party vendors to ensure project alignment and high-quality data delivery.
  8. Create instructional materials for consistency in the labeling process, oversee multimedia content preparation while ensuring compliance, and conduct quality reviews for data accuracy.
  9. Strategically select labeling tools and advocate for additional resources, including hiring specialized personnel, to meet project demands efficiently.
  10. Assist in the mentoring and development of junior AI team members.

1.2 Experience

  1. Bachelor/Masters in Statistics, Mathematics, Computer Science, Machine Learning, or related areas.
  2. 2-5 years of hands-on experience in AI and machine learning projects.
  3. Proven track record of developing and deploying AI models that have resulted in tangible business outcomes.
  4. Experience with machine learning frameworks (such as TensorFlow, PyTorch) and libraries (like scikit-learn, pandas).
  5. Familiarity with cloud services (AWS, Google Cloud, Azure) for AI development and deployment is preferred.
  6. Strong understanding of data structures, algorithms, and software engineering principles.
  7. Experience in working with large datasets and deep learning architectures.

1.3 Personal Skills

  1. Strong proficiency in programming languages such as Python.
  2. Deep understanding of machine learning algorithms and principles, including supervised and unsupervised learning, neural networks, and natural language processing.
  3. Excellent analytical and problem-solving skills.
  4. Ability to work collaboratively in a team environment and communicate effectively with both technical and non-technical team members.
  5. Strong organizational skills and the ability to manage multiple projects simultaneously.
  6. A continuous learner with a passion for staying at the cutting edge of AI technology.

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