AI Specialist
HubBroker IT Solutions Private Limited
- Ahmedabad, Gujarat
- Permanent
- Full-time
- Machine Learning Development: Design, build, train, and fine-tune machine learning and deep learning models, particularly in the context of large language models (LLMs).
- Data Pipeline Creation: Develop and manage efficient data pipelines for data preprocessing and feature engineering.
- MLOps Implementation: Create CI/CD pipelines to automate the deployment, monitoring, and updating of ML models in production environments.
- LLM Fine-Tuning: Fine-tune LLMs for specific applications and domains, leveraging frameworks like Hugging Face and open-source LLMs.
- Model Evaluation: Regularly evaluate model performance, accuracy, and reliability using statistical and computational techniques.
- Collaboration: Work in an Agile environment with cross-functional teams to integrate ML solutions into larger systems.
- Framework Utilization: Utilize machine learning frameworks such as TensorFlow, PyTorch, or Keras to develop scalable solutions.
- Data Management: Manage large datasets, ensure data quality, and design robust preprocessing pipelines.
- AI/ML Research: Stay updated on the latest advancements in AI/ML algorithms, tools, and techniques to implement cutting-edge solutions.
- Fundamentals of SQL
- FastAPI framework
- PyTorch framework
- MMDetection framework
- Techniques for parallel execution and data processing
- Optical Character Recognition (OCR)
- Data processing and image manipulation
- Basics of neural networks and optimizer
- Convolutional Neural Networks (CNN)
- Region-based Convolutional Neural Networks (RCNN)
- Prompt engineering principles
- Retrieval-Augmented Generation (RAG) using the LangChain framework
- Open-source Large Language Models (LLMs)
- MLflow
- Docker
- CI/CD pipelines
- GitLab
- AI/ML Expertise: In-depth knowledge of AI/ML algorithms and techniques, including data preprocessing, feature engineering, and model optimization.
- MLOps: Experience with end-to-end ML lifecycle management, including creating CI/CD pipelines for model deployment.
- Frameworks & Libraries: Expertise in machine learning frameworks like TensorFlow, PyTorch, and Keras, and familiarity with libraries for LLMs (e.g., Hugging Face Transformers).
- Distributed Systems: Knowledge of distributed computing systems like Hadoop or Spark.
- LLM Fine-Tuning: Understanding LLM architectures, fine-tuning techniques, and methods for evaluating and monitoring LLM performance.
- Mathematics: Advanced math skills, including linear algebra, Bayesian statistics, group theory, and optimization techniques.
- Data Engineering: Proficiency in data modeling, data architecture, and preprocessing pipelines.
- Communication: Strong written and verbal communication skills.
- Problem-Solving: Outstanding analytical and problem-solving abilities.
- 5-day working company.
- Quarterly rewards based on roadmap achievements and customers’ success.
- 20 Yearly leaves.
- 14 National Holidays Off.
- Cross-team work culture.
- Career Development & Training Programs.
- Employee Referral Benefits.
- Birthday/Anniversary/Festival Celebrations.
- Compensatory Off Benefits.
- Paid half-day leaves on special occasions of Birthdays & anniversaries.
- Meals while working extra.
- Yearly day-outing activities.
- Yearly Achievement Awards.