
Generative AI/ML Engineer
2 days ago
Job Title:
Generative AI/ML Engineer – Synthetic Data, Behavioural Simulation & Digital Twins
Location: Delhi NCR (Noida) | Onsite Mandatory
Experience: 1+ Years
Type: Full-Time
Immediate Joiner Preferred
About Us
Acutus AI is on a mission to transform decision-making through AI-generated behavioural simulations. Our flagship product, ZCoded, helps businesses simulate how digital personas (your next-gen consumers) think, feel, and act
before launching products or campaigns in the real world
. We're building digital twins of consumers and training them using real-world behaviour, not just demography.
Your Role
As an early Generative AI/ML Engineer at Acutus AI, you'll be at the heart of building ZCoded's simulation engine. You'll work on
persona modelling, behavioural prediction and synthetic data generation
using state-of-the-art AI techniques like GANs, VAEs, LLMs and multi agents. This is a builder role, you'll own modules end-to-end, experiment fast and iterate live with feedback from early clients.
What You'll Build
- Generative models to simulate consumer decision-making pathways (GANs, VAEs, LLM)
- Fine-tuned persona embeddings from real-world behavioural data
- A digital twin system capable of simulating web journeys, media engagement and purchase decisions
- Integrations with scenario-based testing modules
- Lightweight RESTful APIs to serve simulations into client-side apps or analytics tools
What We're Looking For
Must-Have
- 1+ years of hands-on experience with Gen AI or ML/DL (internships and projects count)
- Familiarity with PyTorch or TensorFlow
- Hands-on experience in:
- Generative models (GANs, VAEs)
- LLMs, prompt engineering, multi-agent, RAG
- Reinforcement learning or agent-based modelling
- Knowledge of libraries such as HuggingFace Transformers, Langchain, or Scikit-learn
- Strong Python fundamentals and experience working with unstructured data
- Hunger to build from scratch and get hands dirty in a startup environment
Nice-to-Have
- Experience with consumer behaviour modelling, NLP pipelines or recommender systems
- Worked on synthetic data, simulated environments or AI-based persona engines
- Familiarity with MLOps (Docker, MLflow, GitHub Actions)
Why Join Us
- Skin in the game: Join as part of the core founding team
- Work that matters: Your code will simulate human behaviour; before brands spend real-world money
- Move fast, learn faster: No silos, no red tape. Build. Ship. Repeat.
- Tech + Imagination: Be part of redefining how consumer research happens in the age of AI
How to Apply
Drop us a note at [] with your resume, GitHub/portfolio (if any)
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