GenAi Specialist

Hello,

I hope this message finds you well.

I’m reaching out to share an exciting opportunity that I believe aligns with your experience and expertise in the field for my client. If you are interested, I’d love to connect and share more details.

We are seeking a highly skilled GenAI Specialist to lead the development and deployment of cutting-edge generative AI models. This role is pivotal in advancing our AI capabilities, leveraging state-of-the-art techniques in natural language processing (NLP), computer vision, and generative modeling to solve complex problems. The ideal candidate will bring technical expertise, creativity, and a passion for innovation to drive impactful projects.

Develop and fine-tune generative AI models, such as large language models (LLMs) and GANs, for specific use cases.

Research and implement advanced techniques in AI, including transfer learning, reinforcement learning, and multimodal AI.

Design and optimize model architectures to enhance performance, scalability, and efficiency.

Collaborate with cross-functional teams to integrate GenAI solutions into applications and systems.

Build and maintain pipelines for data collection, preprocessing, and annotation to support model training.

Conduct experiments to evaluate model performance and implement continuous improvements.

Stay up-to-date with advancements in GenAI research and tools, incorporating them into projects as appropriate.

Ensure compliance with ethical AI standards and address bias in datasets and model predictions.

Create detailed documentation of methodologies, findings, and best practices for internal and external stakeholders.

Provide mentorship and technical guidance to team members working on GenAI projects.

Qualifications

Education:

Education qualifications listed below will be considered but are not required.

Master’s or Ph.D. in Artificial Intelligence, Machine Learning, Computer Science, or a related field.

Experience:

3+ years of experience in developing generative AI solutions or working with large-scale machine learning models.

Proven track record of deploying AI models in production environments.

Technical Skills:

Proficiency in machine learning frameworks and tools (e.g., TensorFlow, PyTorch, Hugging Face).

Expertise in natural language processing (NLP), transformers, and multimodal AI.

Experience with large-scale datasets and distributed computing frameworks (e.g., Spark, Dask).

Strong programming skills in Python and familiarity with libraries like NumPy, pandas, and Scikit-learn.

Knowledge of cloud platforms and AI infrastructure (e.g., AWS Sagemaker, Google Cloud AI).

Familiarity with MLOps practices for model deployment, monitoring, and management.