Lead-AI Engineer

About Us: At CLOUDSUFI, a Google Cloud Premier Partner, we are a Data Science and Product Engineering organization dedicated to building innovative products and solutions for the Technology and Enterprise industries. Our core belief is in the transformative power of data to drive business growth and facilitate better decision-making processes. With a unique blend of expertise in business processes and cutting-edge infrastructure, we collaborate with our clients to extract value from their data and optimize enterprise operations. Our Values: We are a team driven by passion and empathy, placing high importance on human values. Our mission is to enhance the quality of life for our employees, customers, partners, and the community at large. Equal Opportunity Statement: Role: Lead AI Engineer Location: Noida, Delhi/NCR (Hybrid) Experience: 5-10 years Role Overview: As a Senior Data Scientist / AI Engineer at CLOUDSUFI, you will play a pivotal role in our technical leadership team. Your primary responsibility will be to conceptualize, develop, and implement advanced AI and Machine Learning solutions, focusing on areas such as Generative AI and Large Language Models (LLMs). You will be tasked with designing and managing scalable AI microservices, leading research into cutting-edge techniques, and translating intricate business requirements into impactful products. This position demands a combination of profound technical proficiency, strategic thinking, and leadership qualities. Key Responsibilities: - Architect & Develop AI Solutions: Build and deploy robust and scalable machine learning models, emphasizing Natural Language Processing (NLP), Generative AI, and LLM-based Agents. - Build AI Infrastructure: Develop and manage AI-powered microservices utilizing frameworks like Python FastAPI to ensure optimal performance and reliability. - Lead AI Research & Innovation: Keep abreast of the latest AI/ML advancements, spearhead research endeavors to assess and implement state-of-the-art models and techniques for enhanced performance and cost efficiency. - Solve Business Problems: Collaborate with product and business teams to identify challenges and devise data-driven solutions that drive significant business value, such as constructing business rule engines or predictive classification systems. - End-to-End Project Ownership: Take charge of the complete lifecycle of AI projects from conceptualization, data processing, model development to deployment, monitoring, and continuous iteration on cloud platforms. - Team Leadership & Mentorship: Drive learning initiatives within the engineering team, provide guidance to junior data scientists and engineers, and establish best practices for AI development. - Cross-Functional Collaboration: Work closely with software engineers to seamlessly integrate AI models into production systems and contribute to the overall system architecture. Required Skills and Qualifications: - Master's (M.Tech.) or Bachelor's (B.Tech.) degree in Computer Science, Artificial Intelligence, Information Technology, or a related field. - 6+ years of professional experience in roles such as Data Scientist, AI Engineer, or similar. - Proficiency in Python and its core data science libraries (e.g., PyTorch, Huggingface Transformers, Pandas, Scikit-learn). - Hands-on experience in building and fine-tuning Large Language Models (LLMs) and implementing Generative AI solutions. - Expertise in developing and deploying scalable systems on cloud platforms, particularly AWS, with experience in GCS as a bonus. - Strong background in Natural Language Processing (NLP), including multilingual models and transcription. - Familiarity with containerization technologies, specifically Docker. - Solid understanding of software engineering principles and experience in building APIs and microservices. Preferred Qualifications: - Strong project portfolio with a track record of publications in reputable AI/ML conferences. - Experience in full-stack development (Node.js, Next.js) and various database technologies (SQL, MongoDB, Elasticsearch). - Knowledge of setting up and managing CI/CD pipelines (e.g., Jenkins). - Proven leadership skills in guiding technical teams and mentoring fellow engineers. - Experience in developing custom tools or packages for data science workflows.,