Job Description: | As an experienced engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to conduct statistical analyses on business processes using machine learning (ML) techniques makes you an integral part of delivering a customer-focused solution. Your technical knowledge and desire to problem-solve to support the next generation of systems. As a machine-learning engineer on our team, you will train, test, deploy, and maintain models that learn from data.
In this role, you will own and define the direction of mission-critical solutions by applying best fit ML algorithms and technologies. You will be part of a large community of machine learning engineers across the company and collaborate with data engineers, data scientists, solutions architects, and subject matter experts to deliver world-class solutions to process data and information to provide near real-time analysis. Your advanced and extensive technical expertise will guide clients as they navigate the landscape of ML algorithms, tools, and frameworks.
Experience in AI, Python programming, and deep learning frameworks, including PyTorch, MXNet, TensorFlow, or Keras, and big data technologies
Experience with developing Natural Language Processing (NLP), Large Language Model (LLM), and Retrieval-Augmented Generation (RAG) enabled solutions
Experience in working with API services for serving NLP and analytical models, including Flask or Fast API
Experience with DevOps Tools, including Docker, K8s, or Gitlab CI/CD
Knowledge of AI-enabled systems
Knowledge of AI concepts, including clustering, regression, algorithm selection, and evaluation
Ability to address unbounded technical issues and problem solve
Experience with HTML, CSS, and front-end web frameworks
Experience with MS Copilot Studio, Amazon Web Services (AWS) or Azure AI and ML services, including Bedrock and Sagemaker
Experience with working in enterprise systems
Experience with Data Operations, such as analytics, engineering, or platform
Knowledge of artificial intelligence principles and practices, including deploying ML models into production
Ability to evaluate algorithm performance
Security, Cloud, Software Development, AI and ML, Computer Vision, Deep Learning, or NLP Certification |