AI/ML Engineer

3 weeks ago

bangalore, India Optimal Virtual Employee Full time

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

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