Generative AI Engineer

Company Description TRKFLY AI is an autonomous AI platform designed to empower creators, learners, and businesses through a suite of specialized products. PulseAI supports content creators, influencers, brands, and businesses in producing content, analyzing engagement, discovering trends, and scaling across social media. TRK LearnAI offers an AI-powered engineering learning ecosystem with tailored roadmaps and personalized learning paths. OMNISCIENCE DS acts as an autonomous multi-agent data scientist, converting raw datasets into production-ready machine learning systems. HELIOS BI delivers autonomous analytics by generating KPIs, forecasts, dashboards, and business recommendations from raw data, making elite-level AI accessible to a broad audience.

Role Description The Generative AI Engineer will design, build, and optimize generative AI models that power TRKFLY AI’s products, including content creation, learning personalization, data science automation, and business intelligence capabilities. This full-time role is on-site in Hyderabad and involves developing model architectures, training and fine-tuning large language and multimodal models, and integrating them into production-grade systems. The engineer will collaborate closely with product, data science, and engineering teams to translate business requirements into robust AI solutions, perform rigorous experimentation, and ensure model reliability, safety, and performance. Day-to-day activities include writing clean, efficient code; conducting model evaluation and benchmarking; implementing MLOps best practices; and contributing to the continuous improvement of TRKFLY AI’s autonomous AI platform.

Qualifications

• Strong foundation in computer science, mathematics, and machine learning, including deep learning, probability, statistics, and optimization.
• Hands-on experience with generative AI (e.g., large language models, diffusion models, transformers) and frameworks such as PyTorch or TensorFlow.
• Proficiency in programming languages commonly used in AI/ML development, such as Python, and familiarity with software engineering best practices (version control, testing, code review).
• Experience building and deploying end-to-end ML pipelines, including data preprocessing, model training, evaluation, and production deployment on cloud or scalable infrastructure.
• Knowledge of MLOps tools and practices (e.g., experiment tracking, model monitoring, CI/CD for ML, containerization) to support reliable and maintainable AI systems.
• Ability to work with large datasets, perform data analysis, and collaborate with data scientists and engineers to refine features and model inputs.
• Strong problem-solving skills, clear technical communication, and the ability to collaborate effectively in a cross-functional, on-site team environment.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Electrical Engineering, or a related field; relevant industry experience in AI/ML or applied research is