AI Engineer

Company Description HopfieldAI began as a deep-tech research collective focused on neural networks, deep learning, and natural language processing, and has evolved into an AI-native tech studio creating original intellectual property for global products. The team operates at the intersection of cutting-edge research and practical product development, supporting ideas with long-term commitment and rigor. Its portfolio includes AI-driven ventures such as Avenu.ai, ModernMT.com, Hana.health, AutoBIQ.com, and Yoska. HopfieldAI also emphasizes collaboration and design-focused retreats through Hopfield.work, fostering an environment where engineering talent can work closely with researchers, designers, and product teams.
Role Description The AI Engineer will design, build, and optimize machine learning and deep learning models that power production-grade products across HopfieldAI’s portfolio. Day-to-day responsibilities include implementing and evaluating neural architectures, developing NLP and pattern recognition pipelines, writing high-quality, scalable code, and collaborating with cross-functional teams to integrate AI components into software systems. The role also involves conducting experiments, analyzing model performance, and contributing to research-driven features and prototypes. This is a full-time, hybrid role based in Bhubaneswar, where in-office collaboration is complemented by partial work-from-home flexibility.
Qualifications

• Candidates should possess strong foundations in Computer Science and Software Development, including data structures, algorithms, and production-ready coding practices.
• Candidates should possess skills in Neural Networks and Pattern Recognition, with experience training, tuning, and deploying deep learning models.
• Candidates should possess expertise in Natural Language Processing (NLP), including working with modern language models, embeddings, and text-processing pipelines.
• Candidates should possess proficiency in relevant programming languages and tools (e.g., Python, PyTorch/TensorFlow, REST APIs, Git) for end-to-end AI system development.
• Candidates should possess strong analytical and problem-solving abilities, with experience designing experiments, evaluating model metrics, and iterating on solutions.
• Beneficial qualifications include experience with cloud platforms (e.g., AWS, GCP, Azure), MLOps practices, and prior work on research-oriented or IP-heavy AI projects.
• A bachelor’s or master’s degree in Computer Science, Electrical Engineering, Applied Mathematics, or a related field, or equivalent practical experience, is preferred.