Data Scientist

Role & responsibilities

Hope akash meets the requirement.

Design, develop, test, and deploy AI models and systems using various frameworks and tools.

Monitor and evaluate the performance and accuracy of AI models and systems in production.

Identify and troubleshoot issues related to data quality, model drift, scalability, and reliability.

Optimize and automate the AI model lifecycle using MLOps best practices.

Collaborate with data scientists, ML engineers, and business stakeholders to understand the requirements and objectives of AI projects.

Research and implement new AI techniques and methodologies to improve the existing solutions and explore new opportunities.

Research and Development: Stay abreast of the latest advancements in AI/GenIA, explore novel applications, and develop proof-of-concept projects.

Model Selection and Fine-tuning: Select and fine-tune pretrained GenAI models (e.g., GPT4, LLaMa) for specific tasks, including text generation, image creation, code synthesis, etc.

Data Exploration and Preparation: Prepare and analyze data sets for training and evaluation of GenAI models, ensuring data quality and addressing potential biases.

Experimentation and Evaluation: Conduct experiments to assess the performance of GenAI models and compare different architectures and approaches.

Application Integration: Develop and integrate GenAI models into existing or new applications, leveraging frameworks like LangChain for seamless orchestration.

Collaborate with Cross-Functional Teams: Work closely with data scientists, software engineers, product managers, and designers to bring GenAI solutions to life.

Contribute to Knowledge Sharing: Document your findings, share best practices, and contribute to the team's knowledge base.

Preferred candidate profile

Perks and benefits