Senior Applied Research Engineer

2 - 5 years

0 Lacs

Posted:1 day ago| Platform: Foundit logo

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Job Type

Full Time

Job Description

Senior Applied Researcher AI (Computer Vision / Multimodal)

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Spyne is transforming automotive retail with Generative AI. What began with a simple ideahelp dealers sell cars online fasterhas evolved into the world's first AI-powered automotive retail ecosystem, reshaping how 350,000+ dealers market and sell vehicles globally.

$16M

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Research Lead / Senior Applied Researcher (AI/ML/CV)

build the thing nobody has built before

What You Will Work On

You will design foundational models and agent frameworks across:

Generative Vision

  • Premium automotive image creation (Diffusion, 3D, NeRFs, SDFs, Gaussian Splatting)

Voice Intelligence

  • Real-time voice agents (ASR, TTS, latency-optimized dialogue models)

Text Intelligence

  • Reasoning agents for dealer workflows (lead handling, follow-ups, service flows)

Multimodal & Cross-Modal Learning

  • Vision ? Text ? Audio alignment
  • Embeddings, routing models, and representational unification

Self-Improving Systems

  • RLHF pipelines
  • Data-engineered tuning loops
  • Autonomous feedback-driven model refinement

You will be the architect who prototypes, validates, breaks, rebuilds, and productionizes new ideas before they scale across the company.

Your Responsibilities

  • Design and train novel CV, LLM, and multimodal architectures optimized for dealership workflows.
  • Build generative pipelines that convert raw images, video, or speech into structured, high-value outputs.
  • Execute applied research in diffusion models, retrieval-augmented LLMs, 3D reconstruction, and voice models.
  • Produce clean, reproducible research code with rigorous experimentation.
  • Collaborate with infrastructure teams to deploy models at scale with low latency and high uptime.
  • Work closely with the AI Research Manager and Product teams to define future research directions.

Job Requirements

  • PhD in CS/Engineering from a top university OR Master's with strong CV/GANs experience.
  • Publications in peer-reviewed conferences (NeurIPS, CVPR, ICML, ICLR, ICCV, ACL) preferred.
  • 25 years experience in Computer Vision, Deep Learning, Generative Modeling, or LLM research.
  • Deep understanding of diffusion, transformers, 3D vision, and multimodal architectures.
  • Ability to train both large and small language models, and debug complex training behaviours.
  • Strong grounding in optimization, probabilistic modeling, and representation learning.
  • Experience deploying research models to production is a strong advantage.
  • Demonstrated ability to independently explore, prototype, and ship results.

Preferred Background

Experience with one or more of the following:

  • Neural Radiance Fields (NeRFs)
  • Gaussian Splatting
  • Differentiable Rendering
  • Diffusion Models
  • 3D Diffusion / Generative Models
  • Signed Distance Fields (SDFs)
  • Prompt Engineering

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