ETIC, AI Engineer - Associate

Associate In Applied AI Team

As an Associate in our Applied AI team, you will work on building and deploying AI-powered solutions that drive impact for our clients across industries. You'll collaborate with experienced engineers, data scientists, and business stakeholders to turn raw data and innovative ideas into production-ready systems. This is an opportunity to grow your machine learning and software engineering skills in a collaborative, client-focused environment.

• Assist in developing and evaluating machine learning models using Python, scikit-learn, and modern frameworks like PyTorch and Hugging Face Transformers.
• Assist in developing and testing generative AI agents and applications ->
  Lang Chain, Lang Graph.
• Participate in the implementation of retrieval-augmented generation (RAG) pipelines leveraging vector databases.
• Support with prompt engineering, the fine-tuning of foundation models for domain-specific use cases and transfer learning techniques.
• Help generate and use synthetic data for model training, evaluation, and robustness testing.
• Work with data pipelines to preprocess, transform, and structure data for AI applications.
• Collaborate with engineers and data scientists to build backend services and APIs for deploying AI models.
• Use Git for version control and contribute to collaborative software development workflows.
• Participate in Agile development cycles, including sprint planning, daily stand-ups, and code reviews.
• Contribute to documentation, experiment tracking, and explainability efforts for AI models.
• Stay up-to-date with emerging trends in LLMs, GenAI, and responsible AI practices.

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field.
• Solid programming skills in Python, including use of libraries like Pandas, Num Py, and Matplotlib.
• Exposure to core machine learning concepts (e.g., regression, classification, model evaluation).
• Understanding of data manipulation, feature engineering, and model evaluation techniques.
• Understanding of how LLMs work, and familiarity with popular tools (e.g., OpenAI, Hugging Face).
• Interest in or basic experience with Lang Chain, vector databases, and RAG frameworks.
• Comfortable working with version control (Git), Jupyter Notebooks, and REST APIs.
• Strong communication skills and a collaborative mindset.

• Hands-on experience with tools like Hugging Face Transformers, Lang Chain, Llama Index, or OpenAI API.
• Familiarity with cloud-based AI tools (e.g., AWS Sage Maker, Azure AI Services, Google Vertex AI).
• Exposure to front-end technologies (e.g., streamlit, nextJS) or back-end frameworks (e.g., Flask, FastAPI).
• Experience with synthetic data generation (e.g., text simulation, data augmentation).
• Familiarity with fine-tuning techniques (e.g., LoRA, PEFT, instruction tuning).
• Coursework or personal projects involving deep learning, NLP, or generative models.
• Basic understanding of containerization (Docker).
• Familiarity with multi agent architectures.

What We Offer

Continuous learning through hands-on experience and formal training in applied AI, MLOps, and GenAI.

Exposure to real-world AI projects with leading clients across industries.

Opportunities to contribute to innovative client-facing AI projects using advanced tools like Lang Chain and vector search.

Mentorship from senior engineers and technical leaders.

A collaborative environment with opportunities to explore cutting-edge technologies and innovative ideas.