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 PythonExperience with machine learning , basic model training, evaluation, and hyperparameter tuningExposure to transformer-based models and libraries like Hugging Face TransformersComfortable working in Jupyter NotebooksGenAI & NLP Basics
Experience working with pre-trained LLMsKnowledge of prompt design , few-shot learning, and use of APIs like OpenAI or CohereML 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 controlBasic understanding of REST APIs and model deployment workflowsGood to Have :
Familiarity with cloud platforms (AWS / GCP)Exposure to ML lifecycle tools like MLflow or SageMakerSome experience working in an Agile or collaborative team environmentIdeal Candidate Traits :
Curiosity to learn and explore new GenAI tools and APIsStrong debugging and problem-solving mindsetAble to work collaboratively while taking ownership of assigned tasks