AI / ML Engineer

THE WORK: Explore new horizons with enthusiasm and curiosity. You will perform independently and become a subject matter expert while actively participating and contributing in team discussions. Your contributions will help provide thoughtful solutions to work-related challenges. This opportunity invites you to engage deeply with advanced Machine Learning, fostering growth and innovation. Join us in shaping the future with your expertise and passion.

Responsibilities: Design and develop AI/ML and Generative AI solutions using Python

Build and deploy applications leveraging Large Language Models (LLMs)

Develop end-to-end pipelines including data ingestion, preprocessing, model integration, and deployment

Implement prompt engineering and fine-tuning strategies for LLMs

Integrate AI services into web/mobile/backend applications via APIs

Work with vector databases and embeddings for semantic search and RAG architectures

Optimize models and pipelines for performance, latency, and cost

Collaborate with cross-functional teams to translate business requirements into AI solutions

Ensure responsible AI practices including data privacy, bias mitigation, and explainability

Monitor and improve model performance in production environments

________________________________________

Required Skills & Qualifications

6-8 years of experience in software engineering / AI / ML, Python roles,

Strong programming expertise in Python

Hands-on experience with ML/DL frameworks like PyTorch or TensorFlow

Experience with LLM frameworks such as LangChain or LlamaIndex

Solid understanding of NLP concepts and transformer-based models

Experience with REST APIs and microservices architecture

Familiarity with vector databases (e.g., Pinecone, FAISS, Weaviate)

Experience with version control systems like Git

________________________________________

Preferred Qualifications

Experience working with APIs from providers like OpenAI or open-source LLMs (Llama, Mistral)

Knowledge of Retrieval-Augmented Generation (RAG) architectures

Experience with model fine-tuning and evaluation techniques

Exposure to cloud platforms (AWS / GCP) for deployment (excluding Azure)

Understanding of containerization tools like Docker

________________________________________

Soft Skills

Strong analytical and problem-solving skills

Ability to translate complex AI concepts into practical solutions

Good communication and stakeholder management skills

Ability to work independently and in collaborative environments

________________________________________

Nice to Have

Experience with AI agents / autonomous workflows

Knowledge of MLOps practices and CI/CD for ML pipelines

Exposure to multimodal AI (text, image, audio models)

Experience with real-time AI applications (chatbots, voice bots, copilots)