Senior ML Research Scientist - NLP/LLM/Generative AI (4-8 yrs)

Responsibilities :

- Being able to fine-tune models, and build your own models from scratch.

- Being able to read and understand new research, and deploy them into a suitable testing environment.

- Ability to create, evaluate, and deploy testing and evaluation frameworks specific to different models.

- Ability to work on various agentic frameworks and build PoCs around them.

- ML System Development : Design, develop, and maintain scalable and efficient machine learning systems, including writing ML services and APIs.

- Model Deployment : Implement and manage the deployment of machine learning models, including transformer-based LLMs, into production environments, ensuring reliability and scalability.

- Infrastructure Management : Collaborate with infrastructure teams to optimize and manage the underlying systems supporting machine learning workflows.

- Data Pipeline Creation : Create robust and efficient data pipelines for collecting, processing, and preparing datasets for machine learning models.

- Collaboration : Work closely with data scientists, researchers, and cross-functional teams to integrate ML solutions into existing software infrastructure.

- Performance Optimization : Continuously optimize and improve the performance of machine learning algorithms and systems.

- Documentation : Develop and maintain documentation for machine learning systems, APIs, and data pipelines to ensure clarity and ease of use for team members.

Responsibilities :

- Work in managing products as part of the SciSpace product suite.

- Partner with product owners in designing software that becomes part of researchers' lives.

- Model real-world scenarios into code that can build the SciSpace platform.

- Test the code that you write and continuously improve practices at SciSpace.

- Arrive at technology decisions after extensive debates with other engineers.

- Manage large projects from conceptualization, all the way through deployments.

- Evolve an ecosystem of tools and libraries that make it possible for SciSpace to provide reliable, always-on, performant services to our users.

- Partner with other engineers in developing an architecture that is resilient to changes in product requirements and usage.

- Work on the user interface side and deliver a snappy, enjoyable experience to your users.

Requirements :

- 4+ years of experience including working on designing multi-component ML-based systems.

- Strong NLP experience working on various research-oriented projects.

- Very strong understanding of various Gen AI-based ML approaches.

- Strong experience working on various ML frameworks like pytorch, tensorflow, huggingface, etc.

- Strong grasp of one high-level language like Python.

- General awareness of SQL and database design concepts.

- Solid understanding of testing fundamentals.

- Strong communication skills.

- Should have prior experience in managing and executing technology products.

Bonus :

- Any research publication in the ML domain is a big bonus.

- Experience on agentic frameworks like autogenic, langgraph, crew, etc.

- Prior experience working with high-volume, always-available web applications.

- Experience working with the cloud.

- Knowledge of cloud platforms such as AWS, GCP, or Azure.

- Experience with deploying small and big ML models in production environments using containerization tools like Docker.

- Experience in Distributed systems.

- Experience working with start-ups is a plus point.