Staff Machine Learning Engineer
Staff Machine Learning Engineer
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Job Description
About Us
Automation Anywhere is a leader in AIpowered process automation that puts AI to work across organizations. The companys Automation Success Platform is powered with specialized AI generative AI and offers process discovery RPA endtoend process orchestration document processing and analytics with a security and governancefirst approach. Automation Anywhere empowers organizations worldwide to unleash productivity gains drive innovation improve customer service and accelerate business growth. The company is guided by its vision to fuel the future of work by unleashing human potential through AIpowered automation. Learn more atwww.automationanywhere
Key Responsibilities:
Develop and optimize machine learning models leveraging NLP Computer Vision and GenAI.
Architect and implement scalable ML pipelines for training validation deployment and monitoring of production models.
Drive the development of largescale ML infrastructure ensuring lowlatency inference and efficient resource utilization across cloud and hybrid environments.
Implement MLOps best practices automating model training validation deployment and performance monitoring.
Work closely with data engineers software engineers and product teams to ensure seamless integration of ML solutions into production systems.
Optimize ML models for performance scalability and efficiency leveraging techniques like quantization pruning and distributed training.
Enhance model reliability by implementing automated monitoring CI/CD pipelines and versioning strategies.
Lead efforts in data acquisition and preprocessing including annotation and refinement of datasets to improve model accuracy.
Stay updated with stateoftheart ML research identifying opportunities to integrate new techniques and technologies into production systems.
Bachelors or Masters Degree in Computer Science Data Science or related fields. Advanced degrees are a plus.
6 years of handson experience in building and deploying machine learning models with a focus on NLP Computer Vision or GenAI solutions.
Proven experience deploying machine learning models into production environments ensuring high availability scalability and reliability.
Proficiency with modern ML frameworks (e.g. TensorFlow PyTorch).
Experience in building ML pipelines and implementing MLOps for automating and scaling machine learning workflows.
Strong programming skills in Python R SQL and experience with big data technologies (e.g. Spark Hadoop) for data processing and analytics.
Basic proficiency in at least one cloudbased ML services (e.g. AWS SageMaker Azure ML Google AI Platform) for training deploying and scaling machine learning models.
Handson experience with containerization (Docker) orchestration (Kubernetes) and model serving platforms (e.g. Triton Inference Server ONNX) for productionready ML deployments.
Familiarity with endtoend ML pipelines including data collection feature engineering model training and model evaluation.
Knowledge of model optimization techniques (e.g. quantization pruning) to improve inference performance on cloud or edge devices.
Excellent problemsolving skills with the ability to break down complex challenges in document extraction and transform them into scalable ML solutions.
Strong communication skills with the ability to articulate ML problems clearly and work autonomously.
Nice to Have:
Experience in finetuning large language models (LLMs) and applying GenAI techniques.
Experience with distributed training techniques to optimize largescale model training across multiple GPUs or cloud environments.
Familiarity with CI/CD pipelines for ML automated model versioning and monitoring tools for performance and drift in production models.
All unsolicited resumes submitted to any @automationanywhere email address whether submitted by an individual or by an agency will not be eligible for an agency fee.
Required Experience:
Staff IC
Employment Type
Full-Time
