AI / ML Engineer

Job Title : AI / ML Engineer (Mid-Level – GenAI Focus)

Location : Noida (WFO)

Experience Level : 3+ Years

Employment Type : Full-Time

Shift Timings : 1 : 00pm- 10 : 00pm

Job Summary :

We are seeking a mid-level AI / ML Developer with practical experience in machine learning, generative AI, and Python-based development . The ideal candidate should have hands-on exposure to working with LLMs , fine-tuning models, implementing ML pipelines, and integrating AI capabilities into products. You will work closely with senior engineers to support feature development, experimentation, and deployment.

Key Responsibilities :

Assist in building and fine-tuning Generative AI models (e.g., GPT, T5, LLaMA, BERT).

Contribute to ML pipelines for training, testing, and deploying models.

Develop and test code using Python , with ML libraries such as scikit-learn, Transformers, or TensorFlow.

Work with embedding models , prompt engineering , and vector databases for semantic search and chatbot-like solutions.

Build notebooks to demonstrate AI workflows and conduct experiments.

Collaborate with backend or DevOps engineers to integrate models into systems or APIs.

Use version control (GitHub) to manage and document changes and experiments.

Stay up to date with the latest in open-source LLMs and GenAI developments .

Required Skills : Technical Expertise

Solid programming in Python

Experience with machine learning , basic model training, evaluation, and hyperparameter tuning

Exposure to transformer-based models and libraries like Hugging Face Transformers

Comfortable working in Jupyter Notebooks

GenAI & NLP Basics

Experience working with pre-trained LLMs

Knowledge of prompt design , few-shot learning, and use of APIs like OpenAI or Cohere

ML Tools

Familiarity with scikit-learn , NumPy , Pandas

(Bonus) Knowledge of LangChain , vector databases (e.g., FAISS, Pinecone)

Software & Collaboration

Hands-on experience with GitHub , version control

Basic understanding of REST APIs and model deployment workflows

Good to Have :

Familiarity with cloud platforms (AWS / GCP)

Exposure to ML lifecycle tools like MLflow or SageMaker

Some experience working in an Agile or collaborative team environment

Ideal Candidate Traits :

Curiosity to learn and explore new GenAI tools and APIs

Strong debugging and problem-solving mindset

Able to work collaboratively while taking ownership of assigned tasks