AI/ML Engineer

Job Title: AI/ML Engineer (Mid-Level – GenAI Focus)Location: Noida (WFO)Experience Level: 3+ YearsEmployment Type: Full-TimeShift Timings: 1:00pm- 10:00pmJob 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 NotebooksGenAI & NLP Basics- Experience working with pre-trained LLMs - Knowledge 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 control - Basic understanding of REST APIs and model deployment workflowsGood 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 environmentIdeal 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

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