Staff Machine Learning Engineer

Automation Anywhere is seeking a Staff Machine Learning Engineer to design, build, and deploy cutting-edge machine learning systems that operate at real-world scale, advancing Generative AI, Natural Language Processing, and Computer Vision capabilities within its industry-leading platform.

Requirements

• 7+ years of hands-on experience designing, building, and deploying machine learning models, with expertise in NLP, Computer Vision, and/or Generative AI solutions
• Proven experience taking ML models from development to production, ensuring scalability, reliability, high availability, and ongoing performance monitoring
• Strong proficiency in Python (required) and working knowledge of R and SQL, with experience leveraging big data technologies (e.g., Spark, Hadoop) for large-scale data processing and analytics
• Deep experience with modern ML frameworks such as TensorFlow and PyTorch, including model training, evaluation, optimization (e.g., quantization, pruning), and inference performance tuning
• Experience building and managing end-to-end ML pipelines, including data ingestion, feature engineering, model training, validation, deployment, and lifecycle management
• Hands-on experience implementing MLOps best practices, including CI/CD for ML, automated model versioning, monitoring for drift/performance, and workflow automation
• Experience with cloud-based ML platforms (e.g., AWS SageMaker, Azure ML, Google AI Platform) for training, deploying, and scaling models in cloud environments
• Practical experience with containerization and orchestration tools (e.g., Docker, Kubernetes) and model serving platforms (e.g., Triton, ONNX) for production-grade deployments
• Experience fine-tuning large language models (LLMs) and applying Generative AI techniques preferred
• Familiarity with distributed training across multi-GPU or cloud environments preferred

Benefits

• Flexible work schedule / remote roles
• Unlimited Personal Time Off
• 12 holidays off per year
• 4 days volunteer time off per year
• Eligible for 4 company Achievement days off per year
• Variety of health care and well-being benefits
• Paid family/parental leave