Senior Engineer, Machine Learning

What you'll do

• Design and implement machine learning models and pipelines for production use.
• Build scalable training, evaluation, and deployment workflows.
• Optimize model inference for latency, throughput, and cost using quantization, caching, and batching.
• Benchmark and profile models across diverse workloads and hardware environments.
• Integrate ML and LLM models into APIs, microservices, and application infrastructures.
• Maintain model-serving infrastructure such as vLLM, ONNX, and custom runtimes.
• Design data pipelines for ingestion, preprocessing, feature engineering, and validation.
• Develop reusable machine learning components, libraries, and frameworks.

What we're looking for

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field with 2+ years of relevant engineering experience.
• Master's degree in Computer Science, Engineering, Information Systems, or a related field with 1+ year of relevant engineering experience.
• PhD in Computer Science, Engineering, Information Systems, or a related field.
• Proficiency in Python and at least one systems language such as C++, Rust, or Go.
• Strong understanding of machine learning fundamentals, transformer architectures, LLMs, and model evaluation.
• Experience with ML frameworks like PyTorch or TensorFlow and experience building scalable software and APIs.
• Experience with LLMs, multimodal models, generative AI, RAG pipelines, and distributed computing in GPU/accelerator environments.
• Knowledge of model optimization (quantization, distillation), vector databases, and containerization tools like Kubernetes and Docker.