Opening For Research Architect LLM

About the Role

We are seeking a highly motivated, dynamic, and experienced Machine Learning Research Architect to join our growing team and lead the development of cutting-edge Generative AI solutions in a cloud-based environment. You will be responsible for designing, implementing, optimizing, and evaluating novel algorithms and architectures for many multi-modal applications, leveraging the latest advancements in LLMs, data handling, and cloud platforms.

Responsibilities:

Research and Innovation: Conduct independent and/or lead research in Generative AI (text, image, audio synthesis), multi-modal models, and agentic frameworks (LangChain, AutoGPT).

Algorithm & Model Development: Architect advanced Generative AI models using Transformers, GANs, VAEs, and diffusion models, with a focus on core LLMs (Gemini, GPT-4/5, LLaMA 2, Claude).

Model Optimization & Data Handling: Train, Evaluate, and Optimize large-scale models using techniques like LoRA, RLHF, and Retrieval-Augmented Generation (RAG), ensuring robust performance and scalability across datasets.

Cloud & MLOps Expertise:  Deploy and manage models on cloud platforms (GCP, AWS, Azure), utilizing MLOps tools (Kubeflow, MLflow) for seamless CI/CD, versioning, and monitoring.

Security & Governance: Implement security best practices and ensure model compliance with data privacy laws (GDPR, CCPA), along with AI bias detection frameworks.

Technical Leadership: Mentor and guide junior researchers and engineers, fostering a collaborative and innovative research environment.

Collaboration and Communication: Collaborate with cross-functional teams, including product managers, engineers, and researchers, to translate research findings into practical cloud-based applications.

Industry Trends: Stay updated on advancements in Generative AI, multi-modal systems, cloud AI services, and model optimization techniques.

Publication and Dissemination: Contribute to the advancement of the field by publishing research findings in top-tier conferences and journals, highlighting cloud-based solutions.

Qualifications:

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

8+ years of experience in applied AI research, with deep expertise in Generative AI, LLMs, and multi-modal models lately

Proven track record of developing and deploying Generative AI models for real-world applications, ideally within a cloud environment. Experience in cloud platforms (AWS, GCP, Azure), and proficiency with cloud-specific AI services.

Strong knowledge of data handling, model training/optimization (LoRA, RLHF, Vector DBs), and MLOps frameworks.

Expertise in Python, and deep learning libraries (TensorFlow, PyTorch, JAX), with a focus on cloud-native solutions.

Excellent communication and presentation skills, with the ability to effectively convey complex technical concepts to both technical and non-technical audiences.

Passion for pushing the boundaries of Generative AI and contributing to the advancement of the field, particularly within the cloud domain.

Bonus Points:

Contributions to open-source projects or publications in top-tier AI conferences and journals, focusing on cloud-based solutions.

Experience with containerization technologies like Docker and Kubernetes.