Artificial Intelligence Researcher (3-5 yrs)

Exp : 3 to 5 Years

Qualification : MCA/B.E/B.Tech (Mandatory to attach higher education certificate to profile)

Mode of work : WFO (5 Days)

NP : 30 to 45 Days

Location : Bangalore and Hyderabad

Job Description :

- 3-5 years of experience in AI/ML research and model development.

- Strong knowledge of machine learning algorithms, deep learning frameworks (e., TensorFlow, PyTorch), and data science techniques.

- Proficiency in programming languages such as Python, R, or C++.

- Proven ability to publish research papers and present findings at conferences.

- Designing and implementing advanced state-of-the-art AI architectures, specializing in LLMs, SLMs, VLMs and MLLMs.

- Develop Gen AI workflows, fine tune and work with stakeholders. Perform scientific evaluation of NLP/LLM models, come up with new techniques for model validation, evaluation, trust and safety.

- Understand user behavior and requirements and develop accordingly.

- Write Generative AI pipelines to give contextual awareness of structured and unstructured data to LLMs.

- Develop MLOps (Machine Learning Operations) workflows for data preparation, deployment, monitoring and retraining. Create and own cloud native API to deploy ML models.

- Craft data warehousing strategy along with instrumenting ETL pipelines for maintaining quality data to be used for Model Training.

- Design and implement A/B experiments - user segmentation, user classification, and tooling to support A/B experiments.

- Research and apply state-of-the-art techniques in Deep Learning and Generative AI Domain.

- Build and enhance NLP pipelines for hierarchical data.

Qualifications :

- 3+ years of working experience developing, deploying, tracking and orchestrating scalable ML/AI solutions.

- Knowledge of core ML stack - Pytorch, tensorflow, sklearn, numpy, pandas, etc.

- Familiarity with experiment tracking tools like Weights & Biases, TensorBoard, or ClearML.

- Familiarity with Generative AI frameworks like Langchain, LlamaIndex, HayStack, etc.

- knowledge of most recent developments and ongoing research in Generative AI domain.

- Experience with RAG and handling hierarchical data (e.g. Codebase) for RAG.

- Ability to leverage both structured (e.g. Repositories, documentation) and unstructured (e.g. forums, blogs) programming related data to provide contextual awareness to AI.

- Experience with utilizing agentic capabilities of LLMs.

- Experience with Graph databases and utilization of Graph Databases to give contextual awareness of structured/unstructured data.

- Experience with IDEs and their extensibilities. Expertise in Generative AI techniques for understanding and generating code/code-related text.

- Knowledge of latest LLMs, Embedding models, Embedding Techniques, Retrieval and Reranking techniques, etc.

- Hands on experience with MLOps tools like Mlflow, CometML, Docker, etc.

- Hand on experience with workflow orchestration tools like Airflow, Prefect, or Databricks, etc.

- Knowledge of API frameworks Django, Flask etc.

- Knowledge of web development tools is a plus.