AI Engineer

NGC is looking for a highly skilled and innovative AI Engineer to join our dynamic AI and Machine Learning team. This is an exceptional opportunity to be at the forefront of artificial intelligence, directly influencing the development of groundbreaking AI and generative AI applications that will have an immediate impact on enterprise business operations and workflows.

About the Role:

As an AI Engineer, you will play a pivotal role in designing, building, and deploying next-generation AI solutions centered around generative models. You will be working on challenging and impactful projects that leverage the latest advancements in generative AI, from model development to integration into core products and services. You will collaborate closely with a multidisciplinary team of engineers, data engineers, machine learning engineers, data scientists, and product managers to push the boundaries of what's possible with AI-driven innovation. This role is ideal for someone passionate about generative AI, eager to solve complex problems, and thrive in a fast-paced, collaborative environment.

Responsibilities:

• Design, develop, and implement advanced generative AI models for text, image, audio, video, code, etc. applications, using frameworks such as Langchain, LlamaIndex, CrewAI, PydanticAI, and model APIs where appropriate.
• Design and develop REST APIs for integrating generative AI models into applications and services, ensuring seamless communication and data exchange between systems.
• Research, prototype, and implement state-of-the-art generative AI architectures and techniques, including GANs, VAEs, Diffusion Models, and Transformer-based models, focusing on optimization and practical application.
• Apply prompt engineering techniques, including Chain-of-Thought, ReAct, and other advanced methodologies to effectively control and guide generative models for desired outputs and behaviors.
• Develop and maintain robust and scalable data pipelines for training, fine-tuning, and evaluating generative models, ensuring data quality, integrity, and efficient processing.
• Integrate generative AI models into production systems, focusing on scalability, reliability, and performance optimization, with an emphasis on AIOps best practices.
• Collaborate with cross-functional teams to define product requirements, develop proof-of-concepts, and seamlessly integrate generative AI solutions into products and services.
• Evaluate the performance of generative models using appropriate metrics and evaluation frameworks, and implement strategies for continuous improvement and refinement.
• Stay at the forefront of generative AI research, monitor industry trends, and proactively explore and evaluate new tools, frameworks, and techniques to enhance our AI capabilities.
• Contribute to building and enhancing our MLOps infrastructure and processes, including model deployment, monitoring, and automated retraining pipelines.

Qualifications:

• Bachelor's or Master's degree in computer engineering, industrial engineering, mathematical engineering, artificial intelligence, machine learning, or related technical field.
• 2+ years of hands-on experience developing generative AI applications such as RAG and AI Agents.
• Deep understanding of core machine learning concepts, algorithms, and deep learning architectures, especially as applied to generative modeling.
• Expert programming skills and practical experience in designing and developing REST APIs and integrating them with applications and services.
• Expertise in Python with familiarity with generative AI frameworks such as LangChain, LlamaIndex, CrewAI, and PydanticAI.
• Proven experience with prompt engineering and applying advanced prompt techniques (Chain-of-Thought, ReAct, etc.) to achieve desired outcomes from generative models.
• Solid understanding of MLOps and AIOps principles and practices for deploying and managing AI models in production environments.
• Expertise and hands-on experience in training or tuning generative AI models and techniques for fine-tuning models such as PEFT, LORA.
• Good understanding of efficient training and deployment of generative AI models and accelerators such as GPUs and TPUs.  
• Good understanding of efficient model serving techniques like TGI, NIM.
• Hands-on experience with Google Cloud Platform (GCP) or other cloud platforms and expertise in deploying and scaling ML models in cloud environments.
• Excellent English communication skills, both written and verbal, with the ability to clearly articulate technical concepts to both technical and non-technical audiences.
• Strong problem-solving, analytical and critical thinking skills with a proactive and results-oriented approach.
• Demonstrated ability to work effectively as a team player in a collaborative and fast-paced environment.

Bonus Points (Nice to Have):

• MSc. in a relevant field with a strong focus on AI research and applications.
• Deep expertise in specific areas of generative AI such as NLU, text-to-image synthesis, audio/video generation, or code generation.
• Familiarity with evaluation metrics and methods specific to generative models (e.g., Context Precision/Recall, BLEU, ROUGE, human evaluation techniques etc.).
• Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes) for model deployment and management in GCP.
• Knowledge of database systems (SQL/NoSQL) and data warehousing solutions within GCP.

Skills:

• Programming Languages: Python (Expert)
• ML/DL Frameworks: TensorFlow, PyTorch, Keras, JAX, HuggingFace
• Generative AI Frameworks: Langchain, LlamaIndex, CrewAI, PydanticAI
• Cloud Platform: Google Cloud Platform (GCP), AWS, Azure
• MLOps/AIOps: Model Deployment, Monitoring, Scalability, Automation
• API Development: REST APIs, Application Integration, Communication Protocols
• Prompt Engineering: Chain-of-Thought, ReAct, Advanced Prompting Techniques
• Communication Skills: Excellent Written and Verbal English
• Soft Skills: Team Player, Collaborative, Problem-Solving, Analytical