Location: Gurgaon, India Job Type: Full-Time 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.
contactus@briskwinit.com