Job Title: Gen AI & Data Science Engineer
Location: Bangalore,Chennai,Hyderabad
Experience: 3 - 5 Years
Job Title: Gen AI & Data Science Engineer
Location: Chennai/Hyderabad/Bangalore.
Experience: 3-5 years
Job Type: Fulltime.
Job Summary:
We are seeking a highly skilled and passionate GenAI
& Data Science Engineer with 3-5 years of experience in Python development,
Generative AI, and Data Science. The ideal candidate will have a strong
background in AI agent workflows, LLM fine-tuning, and Retrieval-Augmented
Generation (RAG) models. You will play a key role in designing, developing, and
deploying cutting-edge AI solutions using frameworks such as Lang Chain, Llama
Index, and Hugging Face.
This role offers the opportunity to work on transformative
AI-driven solutions, leveraging state-of-the-art tools and frameworks to create
impactful solutions in real-world applications.
Key Responsibilities:
·
Design, develop, and deploy AI solutions with a focus
on Generative AI and Data Science.
·
Fine-tune Large Language Models (LLM) and implement
Retrieval-Augmented Generation (RAG) models.
·
Collaborate with cross-functional teams to integrate
AI models into business workflows.
·
Utilize frameworks such as Lang Chain, Llama Index,
and Hugging Face to build scalable AI solutions.
·
Participate in end-to-end AI model development,
including data preprocessing, model selection, training, evaluation, and
deployment.
·
Continuously monitor and optimize the performance of
AI models to ensure they meet business requirements.
·
Work with stakeholders to understand AI requirements
and contribute to solution design and architecture.
·
Stay up to date with the latest advancements in AI
technologies and industry trends.
Qualifications
·
Bachelor’s or Master’s degree in Computer Science,
Data Science, AI, or a related field.
·
3-5 years of professional experience in Python
development, AI, and Data Science.
·
Proven experience with Generative AI, including
fine-tuning LLMs and working with RAG models.
·
Hands-on experience with frameworks like Lang Chain,
Llama Index, and Hugging Face.
·
Strong understanding of machine learning algorithms,
deep learning, and natural language processing (NLP).
· Experience in AI model deployment and scaling in production
environments.
Technical Skills
·
Programming: Python, including libraries like
TensorFlow, PyTorch, Pandas, NumPy, etc.
·
AI/ML Frameworks: Lang Chain, Llama Index, Hugging
Face, etc.
·
Machine Learning Algorithms: Supervised and
Unsupervised Learning, NLP, Reinforcement Learning.
·
Data Engineering: Data preprocessing, data wrangling,
ETL processes.
·
Cloud Platforms: AWS, GCP, Azure (experience with AI
tools on cloud platforms).
·
Version Control: Git, GitHub, GitLab.
·
Familiarity with containerization tools like Docker
and Kubernetes.
Soft Skills
·
Strong problem-solving skills and analytical thinking.
·
Excellent communication and collaboration skills.
·
Ability to work independently and as part of a team.
·
Adaptability to evolving technologies and
requirements.
·
Strong attention to detail and high quality of work.
·
Time management and ability to meet deadlines.
Work Experience
·
3-5 years of experience working in AI, Data Science,
or a related field.
·
Practical experience in working with Generative AI,
LLM fine-tuning, and RAG models.
·
Experience with deployment of AI models in cloud
environments.
·
Proven track record delivering AI-driven solutions to
solve real business problems.
Good to Have
·
Experience with other AI tools and frameworks like
OpenAI GPT, DeepPavlov, or similar.
·
Exposure to data integration and API development.
·
Knowledge of advanced topics in NLP, such as
transformers and attention mechanisms.
·
Experience with building AI-powered applications or
chatbots.
Compensation & Benefits
·
Salary: Competitive base salary based on experience
and skills.
·
Bonus: Annual performance-based bonus.
·
Benefits: Health insurance, paid time off,
work-from-home options, and retirement benefits.
·
Learning & Development: Access to AI and Data
Science training, conferences, and certifications.
Key Performance Indicators (KPIs) & Key Result
Areas (KRAs)
KPIs:
·
Timely delivery of AI projects and solutions.
·
Quality and accuracy of fine-tuned AI models.
·
Successful integration of AI solutions into business
workflows.
·
Continuous improvement in AI model performance
(accuracy, speed, scalability).
·
Stakeholder satisfaction and feedback on AI-driven
solutions.
·
Contribution to knowledge sharing and team
collaboration.
KRAs:
·
AI model development, fine-tuning, and deployment.
·
End-to-end ownership of AI solution delivery.
·
Collaboration with cross-functional teams to define
and implement business requirements.
· Optimization and monitoring of AI solutions in production environments.
Contact: hr@bigtappanalytics.com