Lead Engineer

About the Job As a Lead AI/ML Engineer, you spearhead the design, development, and implementation of advanced AI and machine learning models. Your role involves guiding a team of engineers ensuring the successful deployment of projects that leverage AI/ML technologies to solve complex problems. You collaborate closely with stakeholders to understand business needs, translate them into technical requirements, and drive innovation. Your responsibilities include optimizing model performance, conducting rigorous testing, and maintaining up-to-date knowledge of the latest industry trends. Additionally, you mentor team members, promote best practices, and contribute to strategic decision-making within the organization. Core Responsibilities Client Interaction: Discuss client requirements and develop proposals tailored to their needs. Demonstrations and Workshops: Conduct solution/product demonstrations, POC/Proof of Technology workshops, and prepare effort estimates in line with customer budgets and organizational financial guidelines. Model Oversight: Oversee the development and deployment of AI models, especially those generating content such as text, images, or other media. AI Solutions: Engage in coding, designing, developing, implementing, and deploying advanced AI solutions. Expertise Utilization: Utilize your expertise in NLP, Python programming, LLMs, Deep Learning, and AI principles to drive the development of transformative technologies. Leadership and Initiative: Actively lead projects and contribute to both unit-level and organizational initiatives to provide high-quality, value-adding solutions to customers. Strategic Development: Develop value-creating strategies and models to help clients innovate, drive growth, and increase profitability. Technology Awareness: Stay informed about the latest technologies and industry trends. Problem-Solving and Collaboration: Employ logical thinking and problem-solving skills, and collaborate effectively. Client Interfacing: Demonstrate strong client interfacing skills. Project and Team Management: Manage projects and teams efficiently. Required Skills Skills: Hands-on expertise in NLP, Computer Vision, programming, and related concepts. Leadership: Capable of leading and mentoring a team of AI engineers and researchers, setting strategies for AI model development and deployment, and ensuring these align with business goals. Technical Proficiency: Proficient in implementing and optimizing advanced AI solutions using Deep Learning and NLP, with tools such as TensorFlow, PyTorch, Spark, and Keras. LLM Experience: Experience with Large language Models like GPT 3.5, GPT 4, Llama, Gemini, Mistral, etc. along with experience in LLM integration frameworks like LangChain, Llamaindex, AgentGPT, etc. Deep Learning OCR: Extensive experience implementing solutions using Deep Learning OCR algorithms. Neural Networks: Working knowledge of Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs). Python Expertise: Strong coding skills in Python, including related frameworks, best practices, and design patterns. Preferred Knowledge: Familiarity with word embeddings, transformer models, and image/text generation and processing. Deployment: Experience deploying AI/ML solutions as a service or REST API endpoints on Cloud or Kubernetes. Development Methodologies: Proficient in development methodologies and writing unit tests in Python. Cloud: Knowledge of cloud computing platforms and services, such as AWS, Azure, or Google Cloud. Experience with information security and secure development best practices. Qualifications Bachelor's or higher degree in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field. 8+ years in IT with a focus on AI/ML practices and background.