AI/ML Developer

Description :

Key Responsibilities :

- Develop and implement machine learning models tailored to business needs.

- Develop and fine-tune Generative AI models (e.g., LLMs, diffusion models, VAEs) using platforms like Hugging Face, LangChain, or OpenAI.

- Conduct data collection, cleaning, and pre-processing for model readiness.

- Train, test, and optimize models to improve accuracy and performance.

- Work closely with cross-functional teams to deploy AI models in production environments.

- Perform data exploration, visualization, and feature selection

- Stay up-to-date with the latest trends in AI/ML and experiment with new approaches.

- Design and implement Multi-Agent Systems (MAS) for distributed intelligence, autonomous collaboration, or decision-making.

- Integrate and orchestrate agentic workflows using tools like Agno, CrewAI or LangGraph.

- Ensure scalability and efficiency of deployed solutions.

- Monitor model performance and perform necessary updates or retraining.

Requirements :

- Strong programming skills in Python and experience with libraries like Tensor Flow, PyTorch, Scikit-learn, and Keras.

- Experience working with vector databases (Pinecone, Weaviate, Chroma) for RAG systems.

- Good understanding of machine learning concepts, including classification, regression, clustering, and deep learning.

- Knowledge of knowledge graphs, semantic search, or symbolic reasoning.

- Proficiency in working with tools such as Pandas, NumPy, and data visualization libraries.

- Hands-on experience deploying models using REST APIs with frameworks like Flask or FastAPI.

- Familiarity with cloud platforms (AWS, Google Cloud, or Azure) for ML deployment.

- Knowledge of version control systems like Git.

- Experience with Natural Language Processing (NLP), computer vision, or predictive analytics.

- Exposure to MLOps tools and workflows (e.g., MLflow, Kubeflow, Airflow).

- Basic familiarity with big data frameworks like Apache Spark or Hadoop.

- Understanding of data pipelines and ETL processes