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 CollegeKey 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.(ref : hirist.tech)