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)
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