Description :

Key Qualifications :

Technical Skills :

- Strong Work Experience of 2-5 years in AI domain

- Strong programming skills in Python (preferred), with proficiency in libraries like TensorFlow, PyTorch, or Scikit-learn.

- Knowledge of ML operations (MLOps) and experience in deploying models in production environments.

- Solid understanding of traditional ML models (e.g., regression, SVM, decision trees, random forests).

- Exposure to large language models (e.g., OpenAI GPT, Llama, BERT) and fine-tuning techniques.

- Familiarity with NLP techniques, transformers, and generative AI models.

Data Expertise :

- Hands-on experience with data cleanup, preprocessing, and feature engineering.

- Proficiency with data handling tools such as Pandas, NumPy, and SQL.

Architecture and Systems :

- Understanding of software architecture and experience contributing to system design.

- Knowledge of CI/CD pipelines for AI/ML projects.

- Familiarity with cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes) would be a big plus .

Soft Skills :

- Strong analytical and problem-solving abilities.

- Excellent communication skills with the ability to present ideas effectively.

- Proven ability to work collaboratively in a team-oriented environment.

Education :

- B.Tech/M.Tech/MCA in first Class (CS/IT/ECE) From Tier 1 College

Key Responsibilities :

AI/ML Development :

- Design, implement, and optimize AI pipelines, including data ingestion, preprocessing, model training, and deployment.

- Develop and fine-tune traditional machine learning models and integrate them into production systems.

- Work on cutting-edge projects involving LLMs, including prompt engineering, fine-tuning, and inference optimization.

Data Engineering :

- Perform data cleanup and preprocessing, ensuring data quality and consistency.

- Develop and implement feature engineering pipelines to enhance model performance.

- Collaborate with data engineers to manage large-scale datasets efficiently.

Software Development :

- Write clean, maintainable, and efficient code in programming languages such as Python, or Go.

- Build scalable, robust, and maintainable solutions for AI/ML models and their deployment.

- Contribute to architecture design and participate in code reviews to ensure best practices.

Collaboration and Communication :

- Clearly communicate technical concepts and progress to both technical and non-technical stakeholders.

- Act as a team player, contributing to a collaborative and innovative work environment.

Continuous Learning :

- Stay updated on the latest developments in AI/ML, including advancements in LLMs and model optimization techniques.

- Explore and evaluate emerging AI tools and technologies for potential integration into workflows.