Python AI/ML Developer

Python AI/ML Developer

Benefits

• 5 Days a Week
• Health Insurance
• Flexible Timings
• Open Work Culture
• Workshops & Webinars
• Awards & Recognition
• Festive Celebrations

Key Responsibilities

• Advanced Model Development:

  Design and implement cutting-edge deep learning models using frameworks like PyTorch and TensorFlow to address specific business challenges.

• AI Agent and Chatbot Development:

  Create conversational AI agents capable of delivering seamless, human-like interactions, from foundational models to fine-tuning chatbots tailored to client needs.

• Retrieval-Augmented Generation (RAG):

  Develop and optimize RAG models, enhancing AI’s ability to retrieve and synthesize relevant information for accurate responses.

• Framework Expertise:

  Leverage LLAMAIndex and LangChain frameworks for building agent-driven applications that interact with large language models (LLMs).

• Data Infrastructure:

  Expertise in managing and utilizing data lakes, data warehouses (including Snowflake), and Databricks for large-scale data storage and processing.

• Machine Learning Operations (MLOps):

  Manage the full lifecycle of machine learning projects, from data preprocessing and feature engineering through model training, evaluation, and deployment, with a solid understanding of MLOps practices.

• Data Analysis & Insights:

  Conduct advanced data analysis to uncover actionable insights and support data-driven strategies across the organization.

• Cross-Functional Collaboration:

  Partner with cross-departmental stakeholders to align AI initiatives with business needs, developing scalable AI-driven solutions.

• Mentorship & Leadership:

  Guide junior data scientists and engineers, fostering innovation, skill growth, and continuous learning within the team.

• Research & Innovation:

  Stay at the forefront of AI and deep learning advancements, experimenting with new techniques to improve model performance and enhance business value.

• Reporting & Visualization:

  Develop and present reports, dashboards, and visualizations to effectively communicate findings to both technical and non-technical audiences.

• Cloud-Based AI Deployment:

  Utilize AWS Bedrock, including tools like Mistral and Anthropic Claude, to deploy and manage AI models at scale, ensuring optimal performance and reliability.

• Web Framework Integration:

  Build and deploy AI-powered applications using web frameworks such as Django and Flask, enabling seamless API integration and scalable backend services.

Technical Skills

• Deep Learning & Machine Learning:

  Extensive hands-on experience with PyTorch, TensorFlow, and scikit-learn, along with large-scale data processing.

• Programming & Data Engineering:

  Strong programming skills in Python or R, with knowledge of big data technologies such as Hadoop, Spark, and advanced SQL.

• Data Infrastructure:

  Proficiency in managing and utilising data lakes, data warehouses, and Databricks for large-scale data processing and storage.

• MLOps & Data Handling:

  Familiar with MLOps and experienced in data handling tools like pandas and dask for efficient data manipulation.

• Cloud Computing:

  Advanced understanding of cloud platforms, especially AWS, for scalable AI/ML model deployment.

• AWS Bedrock:

  Expertise in deploying models on AWS Bedrock, with tools such as Mistral and Anthropic Claude.

• AI Frameworks:

  Skilled in LLAMAIndex and LangChain, with practical experience in agent-based applications.

• Data Visualization:

  Proficient in visualization tools like Tableau, Power BI for clear data presentation.

• Analytical & Communication Skills:

  Strong problem-solving abilities with the capability to convey complex technical concepts to diverse audiences.

• Team Collaboration & Leadership:

  Proven success in collaborative team environments, with experience in mentorship and leading innovative data science projects.

Qualifications

• Education:

  Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.

• Experience

  : 3-5 years specializing in deep learning, including extensive experience in PyTorch and TensorFlow.

• Industry Expertise:

  Experience in finance, manufacturing, healthcare, or retail sectors.

• Advanced AI Knowledge:

  Familiarity with reinforcement learning, NLP, and generative models.

Location:

Reporting to: