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Company Description ML Villa is an emerging hub for machine learning innovation, inspired by the dynamic community and knowledge-sharing culture of the LinkedIn ML ecosystem. The organization brings together experts, enthusiasts, and learners to explore cutting-edge AI research, tools, and applications. Team members engage with curated content, including articles, tutorials, and case studies, to stay current in a rapidly evolving field. ML Villa emphasizes collaboration, continuous learning, and career growth for professionals passionate about advancing machine learning. The company offers an environment where individuals can contribute to impactful AI solutions while expanding their technical and professional networks.
Role Description This is a full-time, on-site Generative AI Engineer role based in Delhi. The Generative AI Engineer will design, develop, and optimize machine learning models for text, image, and multimodal generation, with a focus on practical applications and production readiness. Day-to-day responsibilities include data preprocessing, model training and evaluation, prompt and architecture experimentation, and performance tuning. The role involves building robust pipelines, integrating models into existing systems, and collaborating with product, design, and engineering teams to deliver reliable AI features. The Generative AI Engineer will also document methodologies, stay current with the latest research, and help define best practices for responsible and ethical use of generative AI.
Qualifications
- Candidates should possess strong skills in machine learning and deep learning, including experience with generative models (e.g., transformers, diffusion models, VAEs, GANs).
- Candidates should possess practical programming skills in languages such as Python and be comfortable with ML frameworks and libraries (e.g., PyTorch, TensorFlow, JAX).
- Candidates should possess abilities in data handling and experimentation, including data preprocessing, feature engineering, evaluation metrics, and A/B testing.
- Candidates should possess familiarity with software engineering practices such as version control, unit testing, code review, and CI/CD for ML workflows.
- Candidates should possess skills relevant to deploying and scaling models, including experience with APIs, containers, and cloud platforms (e.g., AWS, GCP, Azure) for production environments.
- Candidates should possess strong analytical and problem-solving skills, with the ability to translate product requirements into technical solutions and clearly communicate findings.
- Relevant qualifications include a bachelor’s or master’s degree in Computer Science, Data Science, AI, or a related field, or equivalent practical experience.
- Experience with prompt engineering, LLM fine-tuning, reinforcement learning from human feedback (RLHF), or similar techniques is highly beneficial.
- A demonstrated interest in staying current with generative AI research, contributing to internal knowledge sharing, and adhering to ethical and responsible AI principles is expected.
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