Research Core AI Scientist – Foundation Models

1 day ago

Delhi, Delhi, India Hiresquad Resources Full time

Research Scientist – Core AI - Lead

Locations:
Bangalore / Delhi-NCR / Trivandrum / Mumbai (Onsite)

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.

We are
not
looking for

  • 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.

Interested candidates can share resume to

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