Generative AI Engineer

Job Title: Generative AI Engineer

Location: Gurgaon, India

Job Type: Full-Time

Experience:5+ years in data science, with 3+ years focused on generative AI and

LLM development.

Expected Joining:Immediate to 15 days

Company: One of our reputed clients

About the Role:

We are seeking a highly skilled Generative AI Engineer to join our Gurgaon team to drive

the development of advanced data modelling and AI-driven applications. This role will focus

on designing, implementing, and fine-tuning data generation models that replicate complex

real-world data patterns across structured and unstructured data types. You will work

extensively with generative AI techniques, including large language models (LLMs), to create

privacy-centric solutions, helping to unlock insights from sensitive data while preserving

privacy and security. As a key contributor, you'll collaborate with data engineers, product

managers, and privacy experts to innovate and deliver impactful AI-driven solutions.

Key Responsibilities:

Develop and Optimise Generative AI Models:

Design, implement, and refine deep learning models such as conditional

GANs (cGANs), variational autoencoders (VAEs), and transformer-based

models to simulate real-world data patterns across structured, unstructured,

and time-series data.

Implement and manage large language models (LLMs), including GPT and

BERT-based architectures, for generating, augmenting, and transforming

textual data to meet specific domain requirements, ensuring data security and

compliance.

Lead research and development in privacy-preserving generative models,

including differential privacy techniques and federated learning

frameworks to support secure, decentralised data generation across diverse

use cases.

Fine-Tuning LLMs for Customized Applications:

Apply fine-tuning techniques to adapt LLMs for specific business needs,

such as NLP data augmentation, domain-specific language generation,

and contextual AI tasks, enabling responsive data solutions for finance,

healthcare, and technology sectors.

Experiment with transformer models and innovative LLM techniques like

prompt engineering to create domain-adapted AI applications, enhancing

model accuracy and performance across different use cases.

Incorporate Advanced Generative Techniques:

Leverage emerging techniques, such as Diffusion Models (DDPM), Neural

ODEs, etc.

Implement transfer learning and domain adaptation methodologies to

adapt existing models to new domains, enhancing model applicability and

robustness.

Model Validation, Quality Control, and Privacy Compliance:

Develop and implement robust validation protocols to assess model quality,

fidelity, and privacy standards, including privacy leakage testing, data

fidelity scoring, and membership inference testing.

Ensure that all models and generated data meet compliance standards, such

as GDPR and HIPAA, by embedding privacy-preserving mechanisms into the

model training and validation process.

Conduct continuous model validation to ensure outputs align with industry

benchmarks while addressing privacy regulations specific to high-compliance

sectors like finance and healthcare.

Collaborate on Product Development and Strategy:

Work closely with product managers, privacy experts, and software engineers

to shape and refine our AI-driven solutions, ensuring alignment with strategic

business objectives and compliance requirements.

Provide technical leadership in generative AI advancements, sharing insights

on LLM developments and model implementation best practices to junior data

scientists and engineers.

Required Skills and Qualifications:

Educational Background: Bachelor's or Master's degree in Data Science, Machine

Learning, Artificial Intelligence, or a related field.

Experience:

5+ years in data science, with 3+ years focused on generative AI and

LLM development.

Proven experience in developing, deploying, and fine-tuning generative AI

models, particularly in sensitive data applications.

Technical Skills:

Machine Learning and Deep Learning Expertise: Proficiency with

TensorFlow, PyTorch, and other machine learning frameworks.

Generative AI and LLM Knowledge: Advanced knowledge of GANs, VAEs,

transformer architectures, and privacy-preserving AI techniques.

Programming Skills: Strong proficiency in Python, with experience in data

processing libraries like Pandas and NumPy.

Cloud Infrastructure: Experience with cloud platforms (AWS, Azure, GCP)

for scalable deployment and secure model processing.

Preferred Qualifications:

PhD in a relevant field with research in generative AI, large language models, or

privacy-preserving machine learning.

Publications or patents in LLMs, generative AI, or privacy-preserving data

solutions.

Domain Experience: Knowledge of privacy and compliance requirements within

finance, healthcare, or other regulated industries.

How to Apply:

If you are a proactive and experienced professional looking to make a significant impact in the IT industry, we'd love to hear from you. Please send your resume to [Confidential Information] or apply here directly.