As a seasoned professional, you will play a crucial role in developing cutting-edge AI and machine learning solutions, contributing to the team's success and technical growth.

Role Highlights :

- Lead the development of advanced AI models using state-of-the-art technologies

- Collaborate with cross-functional teams to deploy scalable ML solutions

- Drive innovation through research, experimentation, and implementation of AI techniques

What Youll Do :

- Design and implement AI/ML algorithms to solve complex business challenges

- Deploy and maintain ML pipelines using tools like Airflow and Spark

- Utilize cloud platforms for efficient model training and deployment

- Create interactive data visualizations using tools like Power BI and Tableau

What Were Looking For :

- Experience : 8+ years

- Good to Have : Deep Learning, NLP, Time Series Analysis, MLOps, CI/CD, agentic AI systems

- Soft Skills : Adaptability, ownership, communication, collaboration

Must-Have Skills :

- pandas : Proficiency in data manipulation and analysis using pandas library. Ability to clean, transform, and analyze large datasets with pandas.

- NumPy : Strong understanding of NumPy for numerical computing and array operations. Experience in handling multi-dimensional arrays and mathematical functions with NumPy.

- scikit-learn : Expertise in building machine learning models with scikit-learn. Capable of implementing various algorithms for classification, regression, and clustering tasks.

- TensorFlow : In-depth knowledge of TensorFlow for developing and training deep learning models. Experience in building neural networks and deploying models using TensorFlow.

- PyTorch : Proficient in PyTorch for developing neural network architectures and implementing advanced deep learning techniques. Hands-on experience in training models with PyTorch.

- LLMs : Familiarity with Large Language Models for natural language processing tasks. Ability to work with LLMs for text generation and understanding.

- RAG : Experience in working with Retrieve and Generate models for information retrieval and generation tasks. Proficiency in leveraging RAG architecture for AI solutions.

- prompt engineering : Skilled in designing prompts for generating specific outputs from AI models. Ability to optimize prompt strategies for improved model performance.

- Airflow : Hands-on experience with Apache Airflow for orchestrating complex workflows and data pipelines. Proficiency in scheduling and monitoring tasks using Airflow.

- Spark : Proficient in Apache Spark for big data processing and analytics. Ability to work with distributed datasets and perform data transformations using Spark.

- cloud platforms : Expertise in deploying and managing AI/ML solutions on cloud platforms like AWS, GCP, or Azure. Experience in utilizing cloud services for scalable and reliable model deployment.

- data visualization tools (Power BI, Tableau, Matplotlib, Seaborn) : Proficiency in creating interactive and insightful visualizations using tools like Power BI, Tableau, and Python libraries Matplotlib and Seaborn. Ability to present complex data in a clear and engaging manner.