Job
Description
As an AI/ML Engineer at Griphic, you will be responsible for leading the design and development of core AI features, architecting scalable ML systems, mentoring a team of engineers, and collaborating with product and design teams to deliver AI features that enhance user experiences. You will work in a fast-paced startup environment where you will need to make pragmatic trade-offs and continuously ship new features. **Key Responsibilities**: - Lead the design and development of core AI features, covering data ingestion to real-time inference for production products. - Architect scalable, cost-efficient, and observable ML systems and services. - Mentor and guide a team of engineers in technical design, model evaluation, and best practices. - Build pipelines for LLM, CV, or multimodal applications based on product requirements. - Define model evaluation frameworks including offline metrics, live A/B testing, and user feedback loops. - Collaborate with Software, Data, and Product teams to integrate ML-powered features into products. - Deploy and monitor models using containerized microservices, ensuring low-latency inference and reproducibility. - Own incident response and postmortems for AI systems to improve reliability and reduce MTTR. - Optimize training/inference costs through techniques like batching, quantization, and GPU scheduling. - Provide leadership on architecture decisions, research, and scaling strategy. **Qualifications**: - 5+ years of experience in applied ML/AI roles, with at least 2 years in a leadership or mentoring capacity. - Proficiency in Python and at least one deep-learning framework such as PyTorch or TensorFlow. - Experience with end-to-end ML pipelines including data preparation, training, evaluation, deployment, and monitoring. - Track record of successfully delivering ML-powered products to real users. - Familiarity with MLOps tooling and containerized deployments (Docker, ECS, K8s). - Strong statistical fundamentals, experimentation skills, and ability to interpret real-world feedback. - Experience optimizing GPU inference and familiarity with observability stacks and production logging/metrics. - Clear and concise technical communication skills to explain trade-offs and align teams efficiently. **Nice to Have**: - Previous experience in a startup or early-stage product environment. - Knowledge of data privacy, compliance, and security best practices in AI systems. - Interest in shaping AI architecture for a growing product organization. - Strong design-for-users mindset, focusing on shipping usable ML features quickly and iterating. At Griphic, you will be part of a team founded by IIT Delhi engineers, aiming to enrich lives through technological innovation. The company combines advanced AI with hyper-realistic virtual experiences to solve problems and disrupt industries. With a diverse team including AI/ML experts, VR developers, and 3D specialists, Griphic is building the future of immersive web applications. *Note: For more information on the company and to apply for the position, please visit the Google Form provided in the Job Description.* As an AI/ML Engineer at Griphic, you will be responsible for leading the design and development of core AI features, architecting scalable ML systems, mentoring a team of engineers, and collaborating with product and design teams to deliver AI features that enhance user experiences. You will work in a fast-paced startup environment where you will need to make pragmatic trade-offs and continuously ship new features. **Key Responsibilities**: - Lead the design and development of core AI features, covering data ingestion to real-time inference for production products. - Architect scalable, cost-efficient, and observable ML systems and services. - Mentor and guide a team of engineers in technical design, model evaluation, and best practices. - Build pipelines for LLM, CV, or multimodal applications based on product requirements. - Define model evaluation frameworks including offline metrics, live A/B testing, and user feedback loops. - Collaborate with Software, Data, and Product teams to integrate ML-powered features into products. - Deploy and monitor models using containerized microservices, ensuring low-latency inference and reproducibility. - Own incident response and postmortems for AI systems to improve reliability and reduce MTTR. - Optimize training/inference costs through techniques like batching, quantization, and GPU scheduling. - Provide leadership on architecture decisions, research, and scaling strategy. **Qualifications**: - 5+ years of experience in applied ML/AI roles, with at least 2 years in a leadership or mentoring capacity. - Proficiency in Python and at least one deep-learning framework such as PyTorch or TensorFlow. - Experience with end-to-end ML pipelines including data preparation, training, evaluation, deployment, and monitoring. - Track record of successfully delivering ML-powered products to real u
