AI-Engineer (GenAI)

We are seeking a talented and motivated Junior GenAI Engineer with 3-5 years of professional experience to join our innovative and growing team. In this role, you will play a crucial part in designing, developing, and deploying advanced Generative AI models, with a particular focus on Text Analytics, Natural Language Processing (NLP), and Deep Learning techniques. You will work on challenging problems that directly impact our products and services, contributing to the next generation of intelligent systems.

Roles & Responsibilities:

• Model Development & Implementation:

• Data Preprocessing & Feature Engineering:

• Experimentation & Optimization:

• Research & Innovation:

• Deployment & MLOps (early exposure):

• Collaboration & Communication:

• Documentation:

Educational qualification:

Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related quantitative field.

Experience :

• Experience: 3-5 years of professional experience in roles focused on Machine Learning, Deep Learning, Natural Language Processing, or Text Analytics.

Mandatory/requires Skills :

Strong Foundation in NLP & Text Analytics:

• Solid understanding of core NLP concepts (e. g. , tokenization, stemming, lemmatization, parsing, named entity recognition, sentiment analysis).

• Experience with various NLP techniques and libraries (e. g. , NLTK, SpaCy, Transformers).

• Proven ability to work with large unstructured text datasets.

Deep Learning Expertise:

• Hands-on experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX.

• Proficiency in designing and implementing various neural network architectures (e. g. , CNNs, RNNs, LSTMs, Transformers).

• Understanding of key deep learning concepts like backpropagation, optimization algorithms, and regularization.

Generative AI Interest/Exposure:

• Strong interest in and foundational understanding of Generative AI concepts (e. g. , LLMs, diffusion models, GANs, VAEs, attention mechanisms, specialized models to support multi-modality).

• Experience working with pre-trained language models (e. g. , BERT, GPT, T5) for fine-tuning and adaptation.

• Experience with model fine-tuning techniques like LoRA, Q-LoRA, tools like LlamaFactory for model fine-tuning

• Exposure to Agentic AI-based design patterns, prompt engineering and platforms to build multi-agentic systems, e. g. LangGraph, Smolagents, CrewAI, Autogen, n8n

• Evaluation techniques for Agentic systems like using LangSmith

• Strong interest in building tools using popular standards like MCP, A2A, ACP etc.

Programming Proficiency: Expert-level proficiency in Python, including relevant libraries for data science and machine learning (NumPy, Pandas, Scikit-learn).

Problem-Solving Skills: Excellent analytical and problem-solving abilities, with a keen eye for detail and a data-driven approach.

Communication Skills: Strong verbal and written communication skills, with the ability to explain complex technical concepts clearly to both technical and non-technical audiences.

Team Player: Ability to work effectively in a collaborative team environment and contribute to a positive and innovative culture.

Preferred Skills :

• Experience with cloud platforms (AWS, Azure, GCP) for deploying and managing AI/ML workloads.

• Familiarity with LLMOps, MLOps principles and tools (e. g. , MLflow, Kubeflow, Docker, Kubernetes).

• Experience with distributed computing frameworks (e. g. , Spark, Dask).

• Contributions to open-source projects in NLP or Generative AI.

• Published research papers or participation in Kaggle competitions related to NLP/Deep Learning.

• Experience with prompt engineering and fine-tuning large language models for specific tasks.