Sr. AI Research Scientist
Bengaluru, Karnataka, India
Weekday
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Salary range: Rs 2800000 - Rs 6000000 (ie INR 28-60 LPA)
Min Experience: 4 years
Location: Bengaluru
JobType: full-time
We are looking for a highly skilled Senior AI Research Scientist with deep expertise in NLP, Generative AI, and ML system design. The ideal candidate will have a strong research background, experience in developing and fine-tuning machine learning models, and the ability to translate cutting-edge AI advancements into production-ready solutions.
Requirements
Key Responsibilities:
Research & Model Development:
- Fine-tune and develop machine learning models from scratch.
- Read and analyze new AI research papers, extracting insights and deploying them in suitable testing environments.
- Design, evaluate, and implement custom testing and evaluation frameworks for different AI models.
- Work with agentic frameworks and develop Proof of Concepts (PoCs) around them.
ML Engineering Responsibilities:
- ML System Development: Design, develop, and maintain scalable and efficient ML systems, including writing ML services and APIs.
- Model Deployment: Implement and manage the deployment of transformer-based LLMs into production, ensuring reliability and scalability.
- Infrastructure Management: Optimize and manage the infrastructure supporting ML workflows in collaboration with relevant teams.
- Data Pipeline Creation: Build robust data pipelines for data collection, processing, and preparation for ML model training.
- Performance Optimization: Continuously optimize ML models and infrastructure for better efficiency and scalability.
- Collaboration: Work closely with data scientists, engineers, and cross-functional teams to integrate ML solutions into existing software.
- Documentation: Develop and maintain comprehensive documentation for ML systems, APIs, and data pipelines.
Backend Engineering Responsibilities:
- Contribute to product development by integrating ML solutions into real-world applications.
- Design and model real-world scenarios into code to enhance platform capabilities.
- Continuously test, optimize, and refine the codebase to improve efficiency and performance.
- Lead large-scale projects from conceptualization to deployment.
- Develop an ecosystem of tools and libraries to support robust AI-driven applications.
- Collaborate with engineers to build a resilient system architecture adaptable to evolving product requirements.
- Enhance the user experience by working on UI and front-end optimizations.
Ideal Candidate Profile:
- 5+ years of experience designing multi-component ML-based systems.
- Strong background in Natural Language Processing (NLP) and experience in AI research-oriented projects.
- In-depth understanding of Generative AI approaches and methodologies.
- Hands-on experience with ML frameworks like PyTorch, TensorFlow, and Hugging Face.
- Proficiency in Python and a strong grasp of software engineering principles.
- Basic understanding of SQL and database design concepts.
- Strong knowledge of testing fundamentals and best practices.
- Excellent communication and collaboration skills.
- Proven track record in leading and executing technology-driven products.
Bonus Skills:
- Research publications in the ML domain.
- Experience with agentic frameworks like AutoGen, LangGraph, CrewAI, etc.
- Prior experience working on high-volume, always-available web applications.
- Expertise in cloud platforms such as AWS, GCP, or Azure.
- Experience deploying ML models in production using Docker and containerization tools.
- Knowledge of distributed systems and large-scale AI infrastructure.
- Startup experience is a plus.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index š°
Tags: APIs Architecture AWS Azure Data pipelines Distributed Systems Docker Engineering GCP Generative AI LLMs Machine Learning ML infrastructure ML models Model deployment Model training NLP Pipelines Python PyTorch Research SQL TensorFlow Testing
Perks/benefits: Startup environment
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