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
