Member of Technical Staff: Machine Learning Engineer

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) Apply To This Job