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Research Core AI Scientist – Foundation Models / Deep Learning

10 years

0 Lacs

delhi india

Posted:3 days ago| Platform: Linkedin logo

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Skills Required

research ai learning training optimization design inference profiling ml algorithms development sequence reasoning evaluation algebra probability pytorch tracking code planning evidence coordination evaluator quantization distillation vision scaling data video

Work Mode

On-site

Job Type

Full Time

Job Description

Research Scientist – Core AI - Lead

Locations:

Experience : 10+ years


What you’ll do

  • Invent

    new methods in

    deep learning/foundation models

    (architectures, training objectives, optimization, alignment, evaluation).
  • Own the

    research cycle

    end-to-end: literature review → hypothesis → method design → experiments &

    ablations

    → paper →

    open-source

    artifacts → transfer to product teams.
  • Build rigorous

    evaluation

    : benchmarks, baselines, statistical tests, reproducibility (seeds, configs, logs).
  • Collaborate with engineers to scale training & inference (distributed training, profiling, efficiency).


Must-have (strict)

  • PhD (preferred) or MS (Research) in AI/ML/CS


  • First-author, peer-reviewed papers proposing new models/algorithms/objectives in top venues (NeurIPS/ICML/ICLR/ACL/EMNLP/TMLR/JMLR) within the last 3–4 years.


  • Demonstrated from-scratch development for tabular/structured problems: e.g., novel sequence/tabular transformers, time-series objectives, structure-aware pretraining, new loss/regularizers, or agentic reasoning/evaluation methods beyond RAG/prompting.


  • Strong math & systems: linear algebra, probability, optimization; PyTorch or JAX, distributed training, experiment tracking; clean research code and ablation hygiene.


Agentic AI (required exposure)

  • Research experience with

    agentic systems

    (single or multi-agent) covering

    planning, tool-calling, self-critique/evaluators, safety/guardrails

    , or

    learning-to-reason

    —with

    novelty

    beyond wiring APIs.
  • Evidence of

    method contributions

    (e.g., new planner/objective, coordination mechanism, evaluator metric) on

    structured/tabular

    tasks.


Nice to have

  • Work on

    efficiency

    (flash-attn, quantization, LoRA/QLoRA, distillation),

    alignment

    (RLHF/DPO/ORPO), or

    multimodal

    (vision-language/audio).
  • Experience designing

    scaling laws

    , data curriculum, or

    safety/robustness

    evaluations.


not

  • Computer-vision-heavy

    profiles (image/video-centric portfolios).
  • Roles limited to

    prompting/RAG/agent wiring

    without novel methods or first-author papers.
  • Only application/survey papers;

    no code or ablations

    to reproduce claims.


sandhia@hiresquad.in

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