Job Description
<p><p>The ideal candidate will have a solid foundation in software engineering, AI/ML technologies, and software development processes.
The Candidate will be responsible for guiding a team of 4-5 AI developers, ensuring the delivery of robust AI solutions while maintaining high standards in architecture, coding practices, and project execution.<br/><br/><b>Required AI/ML Skills : </b><br/><br/><b>Generative AI (GenAI) : </b><br/><br/>- Experience with Large Language Models (LLMs) like GPT, BERT, or LLaMA.<br/><br/>- Familiarity with fine-tuning LLMs and integrating them into enterprise applications and Databases.<br/><br/>- Knowledge of text generation, summarization, translation, and conversational AI.<br/><br/><b>Traditional Machine Learning : </b><br/><br/>- Proficiency in ML techniques like supervised learning, unsupervised learning, and reinforcement learning.<br/><br/>- Hands-on experience with classification, regression, clustering, and time-series forecasting.<br/><br/><b>AI Frameworks and Tools : </b><br/><br/>- Proficient in frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, scikit-learn, and Keras.<br/><br/>- Familiarity with ML pipelines using tools like MLflow, Kubeflow, or TensorFlow Extended (TFX).<br/><br/><b>Deployment : </b><br/><br/>- Knowledge of containerization (Docker, Kubernetes) and serverless architectures for scalable AI solutions.<br/><br/><b>Required Software Engineering Skills : </b><br/><br/><b>Programming Languages : </b><br/><br/>- Strong proficiency in Python (preferred), Java, or Go for AI application development.<br/><br/>- Experience with API development frameworks such as FastAPI, Django, or Flask.<br/><br/><b>Architectural Concepts : </b><br/><br/>- Deep understanding of microservices architecture, event-driven design, and RESTful APIs.<br/><br/>- Knowledge of distributed systems and high-performance computing.<br/><br/><b>Soft Skills : </b><br/><br/><b>Communication and Presentation : </b><br/><br/>- Excellent verbal and written communication skills, with the ability to simplify complex technical concepts for diverse audiences.<br/><br/>- Strong presentation skills to effectively convey architectural designs and project updates to customers and stakeholders.<br/><br/><b>Team Collaboration : </b><br/><br/>- Proven experience in leading and mentoring technical teams, fostering collaboration, and encouraging continuous learning.<br/><br/>- Ability to work effectively across cross-functional teams including data engineers, product managers, and QA engineers.<br/><br/><b>Key Responsibilities : </b><br/><br/><b>Technical Leadership : </b><br/><br/>- Lead, mentor, and guide a team of AI developers.<br/><br/>- Ensure adherence to best practices in software engineering, AI model development, and deployment.<br/><br/>- Review and approve architectural designs, ensuring scalability, performance, and security.<br/><br/><b>AI Application Development : </b><br/><br/>- Architect and design AI solutions that integrate both Generative AI (GenAI) and traditional Machine Learning (ML) models.<br/><br/>- Oversee the end-to-end development lifecycle of AI applications, from problem definition to deployment and maintenance.<br/><br/>- Optimize model performance, ensure model explainability, and address model drift issues.<br/><br/><b>Architectural Oversight : </b><br/><br/>- Develop and present the big-picture architecture of AI applications, including data flow, model integration, and user interaction.<br/><br/>- Dive deep into individual components, such as data ingestion, feature engineering, model training, and API development.<br/><br/>- Ensure the AI solutions align with enterprise architectural standards and customer requirements.<br/><br/><b>Customer Engagement : </b><br/><br/>- Act as the primary technical interface for customer meetings, providing clear explanations of the AI solutions architecture, design decisions, and project progress.<br/><br/>- Collaborate with stakeholders to understand business needs and translate them into technical requirements.<br/><br/>- Ensure proper documentation, including design documents, code reviews, and testing protocols.<br/><br/>- Monitor project timelines and deliverables, ensuring high-quality outcomes.<br/><br/><b>Qualifications : </b><br/><br/>- Bachelors or Masters degree in Computer Science, AI/ML, Data Science, or related field.<br/><br/>- 6-9 years of experience in developing and deploying AI applications.<br/><br/>- Proven track record of delivering scalable AI solutions in an enterprise setting.</p><br/></p> (ref:hirist.tech)