AI Engineer

As a Trainee AI Engineer at SKO Systems, you will involve supporting the strategic and technical implementation of AI initiatives. The position blends research, experimentation. and operational execution across AI technologies, with a strong emphasis on LLM frameworks and responsible AI practices.

Essential Functions / Deliverables

Understand and Execute AI Directions from Leadership

•            Attend and document AI-related meetings and initiative briefings.

•            Follow technical instructions and break down objectives into research or coding tasks.

•            Seek clarification proactively to ensure alignment with expectations.

Research AI Technologies & Frameworks (LLMs, PyTorch, etc.)

•            Study and summarize capabilities of Large Language Models (LLMs) like GPT, BERT, LLaMA, etc.

•            Explore open-source AI frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers.

•            Compare tools based on use-case fit, performance, and ease of integration.

Support in AI Model Training & Experimentation

•            Assist in preparing/collecting datasets, preprocessing (cleaning/transforming raw datasets) and setting up training pipelines using Python and PyTorch.

•            Run basic training experiments and log results for analysis.

•            Help with hyperparameter tuning and model evaluation under guidance.

•            Utilize version control systems like Git to manage code changes collaboratively.

Contribute to Risk & Feasibility Assessments

•            Document technical challenges, limitations, and potential risks in AI implementation.

•            Research alternatives or workarounds for identified issues.

•            Maintain a risk log and update it based on findings and feedback.

Continuous Learning & Knowledge Sharing

•            Complete internal or external AI training modules (e.g., Coursera, Fast.ai, Hugging Face courses).
•            Stay updated with latest AI research papers, GitHub projects, and tech blogs,

Share learnings with the team through short presentations or documentation

Requirements

Education: Bachelor's degree in computer science, Engineering, or a related field
**Required Years and Area of Professional Experience :**0–1 years of professional experience (on technologies)
Critical Professional Related Technical/Computer Skills :

• Internship or academic project involving AI/ML, NLP, or LLMs

• Exposure to open-source AI libraries like Hugging Face Transformers

• Professional competencies : 
  Python, PyTorch or TensorFlow, LLMs, AI model training workflows, Git, Jupyter Notebooks, and Linux CLI

• Knowledge, Skills & Abilities

·       Knowledge of AI fundamentals, including supervised/unsupervised learning, neural networks, and NLP
·       Ability to research and evaluate AI tools and frameworks for feasibility and applicability
·       Skills in experimenting with models, running training loops, and analyzing results
·       Ability to document technical findings, risks, and recommendations
        Capacity to stay updated with AI trends and contribute to team knowledge sharing **Ethics & Compliance :**This position requires full commitment to fostering the highest standards while promoting an ethical and compliant culture. Integrity, honesty, respectful treatment of others, and willingness to speak up when misconduct or concerning behaviours are evident are essential.