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Associate AI Engineer

Summary

Builds and deploys AI/ML and Generative AI models using Python, TensorFlow, and cloud platforms to solve business problems and enable data-driven decisions.

Job purpose:

This role is responsible for designing, developing, and deploying advanced AI/ML and Generative AI solutions to solve complex business problems. The position focuses on building scalable machine learning models and pipelines while enabling data-driven decision-making across the organization.

Responsibilities:

  • Advanced Data Analysis: Go beyond basic data exploration and delve into complex statistical analysis and modelling techniques using Python libraries like scikit-learn and TensorFlow. Conduct exploratory data analysis to gain insights and inform modelling decisions.
  • Machine Learning Expertise: Architect and implement sophisticated machine learning models to solve real-world and complex problems. Design and implement scalable machine learning pipelines and workflows.
  • Communication & Collaboration: Effectively translate technical findings into clear and actionable insights for technical and non-technical stakeholders. Collaborate with business teams to ensure data-driven solutions align with business objectives
  • Mentorship & Knowledge Sharing: Guide and mentor junior engineers, fostering a collaborative learning environment and sharing best practices within the team. Stay updated with the latest advancements in machine learning research and apply them to improve our solutions.

Skills:

    • Bachelor’s degree in computer science, Data Science, AI, or a related field
    • 1+ years of hands-on experience in AI/ML projects (including internships or academic projects)
    • Proficiency in Python and familiarity with ML libraries such as scikit-learn, TensorFlow, PyTorch, or Hugging Face
    • Basic understanding of machine learning concepts, evaluation metrics, and data preprocessing techniques
    • Experience with MLOps tools such as MLflow or Vertex AI
    • Exposure to cloud platforms (AWS, Azure, or GCP)
    • Familiarity with version control tools such as Git
    • Experience with Jupiter notebooks, APIs, and basic deployment workflows
    • Exposure to GenAI tools and frameworks such as OpenAI, LangChain, or vector databases
    • Strong analytical and problem-solving skills
    • Ability to work in a collaborative and fast-paced environment
    • Strong communication skills
    • Exposure to production-level AI deployments
    • Understanding of model monitoring and optimization techniques

    See also

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