Walk-in || AI ML Engineer

Job description

We are seeking a skilled **Artificial Intelligence**/**Machine Learning Engineer** with strong expertise in Python and cloud platforms to design, develop, and deploy advanced machine learning and generative AI solutions. The ideal candidate will have hands-on experience with deep learning, computer vision, and large language models (LLMs), along with the ability to collaborate effectively across teams. **Key Details** - **Experience:** 3 to 10 years - **Location:** Hyderabad - **Primary Skill:** Python - **Secondary Skills:** AWS / Azure / GCP **Key Responsibilities** - Design and implement scalable data architectures to support machine learning and generative AI workflows. - Fine-tune, optimize, and evaluate large language models (LLMs) and machine learning models. - Apply prompt engineering techniques tailored to specific business use cases. - Collaborate with cross-functional teams to design and build AI-driven solutions. - Break down complex data science problems into manageable tasks and execute them efficiently. - Guide and mentor junior engineers in building data pipelines, datasets, and deploying ML models. - Apply techniques such as NLP, feature engineering, deep learning, and statistical modeling to solve real-world problems. - Use data visualization tools to communicate insights effectively. **Required Technical Skills (Must-Have)** - Strong programming expertise in **Python**. - Experience with ML libraries: **Scikit-learn, NumPy, Pandas, TensorFlow, Matplotlib, Caffe**. - Hands-on experience with deep learning frameworks: **PyTorch, Keras, spaCy**. - Knowledge of deep learning architectures: **CNN, LSTM, Transformers, Self-Attention models**. - Experience in **computer vision and image processing** (mandatory). - Strong understanding of: - Generative AI, LLMs, GPT models - Natural Language Processing (NLP) - Machine learning techniques - Tools: **LangChain, Flask, FastAPI, Jupyter Notebook** - Prompt engineering methodologies - Excellent verbal and written communication skills. - Strong interpersonal and collaboration abilities. **Preferred Skills (Good-to-Have)** - Experience with **vector databases** and graph-based document representations. - Exposure to **MLOps pipelines** and model lifecycle management. - Hands-on experience with **cloud ML platforms** such as AWS SageMaker or Azure ML. - Familiarity with **Docker and Kubernetes**.