AI Research Scientist

Careernet; Bengaluru; Hybrid; INR 1,800,000 - 2,400,000; Full time

Job summary

Careernet is seeking a Research Scientist in AI to implement cutting-edge research into production-ready models for real-world AI applications. You will optimize large-scale models, create robust datasets, and collaborate with engineering and product teams to deploy scalable AI solutions.

The role emphasizes hands-on experience with LLMs, vision and multimodal systems, and a strong foundation in Python, PyTorch, TensorFlow, and JAX.

Qualifications

• Ph.D. or Masters in Computer Science, AI, ML or related field.
• 5–7 years in applied ML/AI roles.
• Proven experience implementing and customizing AI research papers from arXiv/NeurIPS/ICML.
• Hands‑on experience with Large Language Models (LLMs) like GPT, LLaMA, Mistral, Falcon.
• Experience with Vision Models: ViT, SAM, CLIP.
• Experience with Generative Models: Stable Diffusion, DALL•E, GANs.
• Experience with Multimodal systems (vision-language-audio).
• Proficiency in Python, PyTorch, TensorFlow, JAX.
• Experience with Hugging Face Transformers, Diffusers, OpenAI Gym.
• Experience with Weights & Biases, MLflow, TensorBoard.
• Experience with Distributed training: DeepSpeed, FSDP, Horovod.
• Knowledge of Model optimization: quantization, pruning, distillation.
• Experience with Data tools: DVC, Apache Arrow, Label Studio.

Responsibilities

• Implement and customize cutting-edge AI research papers into prototypes and production-ready models.
• Conduct performance experiments on large-scale models: fine-tuning, prompt engineering, architecture changes.
• Develop training/evaluation datasets, including synthetic data generation and benchmarks.
• Collaborate with engineering and product teams to deploy outputs into scalable systems.
• Stay updated with AI advancements and contribute to internal research strategy.
• Document experiments, share insights, and support innovation via reports and patents.

Skills

Python

PyTorch

TensorFlow

JAX

LLMs

Vision Models

Multimodal Systems

GPT/LLM tooling

Prompt engineering

Model optimization

Distributed training

Quantization

Pruning

Distillation

DVC

Apache Arrow

Label Studio

Weights & Biases

MLflow

TensorBoard

DeepSpeed

Horovod

Education

Ph.D. or Masters in Computer Science / AI / ML

Tools

Hugging Face Transformers

Diffusers

Weights & Biases

MLflow

TensorBoard

DeepSpeed

Horovod

DVC

Apache Arrow

Label Studio

OpenAI Gym

Job description

We are seeking a highly skilled and innovative Research Scientist specializing in Artificial Intelligence to join our R&D team. This role is ideal for someone with deep expertise in implementing and customizing state-of-the-art AI research papers, optimizing large-scale models, and building robust datasets. You will work on real-world applications of generative AI, large language models (LLMs), and computer vision systems, contributing directly to the development of scalable and impactful AI solutions.

Key Responsibilities

• Implement and customize cutting-edge AI research papers into working prototypes and production-ready models.
• Conduct performance improvement experiments on large-scale models, including fine-tuning, prompt engineering, and architecture modifications.
• Develop and manage training and evaluation datasets, including synthetic data generation, annotation pipelines, and benchmark creation.
• Collaborate with engineering and product teams to deploy research outputs into scalable systems.
• Stay up-to-date with the latest advancements in AI and contribute to internal research strategy.
• Document experiments, share insights, and support innovation through patent filings and technical reports.

Required Qualifications

• Ph.D. or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• 5–7 years in applied ML/AI roles
• Proven experience in implementing and customizing AI research papers (e.g., from arXiv, NeurIPS, ICML).
• Hands‑on experience with Large Language Models (LLMs): GPT, LLaMA, Mistral, Falcon.
• Experience with Vision Models: ViT, SAM, CLIP.
• Experience with Generative Models: Stable Diffusion, DALL•E, GANs.
• Experience with Multimodal Systems combining vision, language, and audio.
• Proficiency in Python, PyTorch, TensorFlow, JAX.
• Experience with Hugging Face Transformers, Diffusers, OpenAI Gym.
• Experience with Weights & Biases, MLflow, TensorBoard.
• Experience with Distributed training: DeepSpeed, FSDP, Horovod.
• Knowledge of Model optimization: quantization, pruning, distillation.
• Experience with Data tools: DVC, Apache Arrow, Label Studio