What You’ll Do

• Translate cutting-edge research into production-ready machine learning systems

• Design, build, and deploy end-to-end ML models and pipelines

• Develop and optimize models for image and video processing

• Own the full ML lifecycle: experimentation, training/fine-tuning, evaluation, and deployment

• Build low-latency, real-time inference systems and scalable ML infrastructure

• Rapidly prototype using open-source models and adapt them for product needs

• Conduct experiments, analyze results, and iterate to improve performance

• Collaborate with researchers and cross-functional teams (product, engineering, design) to deliver ML solutions at scale

• Stay current with advancements in machine learning and apply them to continuously improve products What We’re Looking For Required Qualifications

• MS/PhD in Computer Science, Electrical Engineering, or related field

• Strong research experience with familiarity in top conferences (e.g., CVPR, ICCV, NeurIPS)

• 5+ years of experience in Python and proficiency in Java, C++, or Scala

• Strong understanding of multi-threading and memory management

• Solid knowledge of ML architectures: CNNs, RNNs (LSTM/GRU), and Transformers

• Experience with PyTorch or TensorFlow

• Experience building end-to-end ML deployment and inference systems, especially for low-latency, real-time applications

• Experience handling large-scale data using tools like Spark

• Experience deploying ML models in cloud environments (AWS preferred)

• Experience with experiment tracking systems and ML workflows Nice to Have

• Experience in low level optimisation, cuda etc.

• Experience productionizing and scaling ML models in real-world systems

• Contributions to open-source projects

• Experience with MLOps tools or distributed training systems

• Familiarity with relational databases (Postgres/MySQL)