Machine Learning Engineer

Summary

Perfict Global is a leading IT consulting services provider focused on innovative workforce solutions for Fortune 500 companies. They are seeking a Machine Learning Engineer to create data platforms and pipelines for advanced analytics, utilizing Azure technologies and collaborating with data scientists to optimize machine learning models.

Responsibilities

• Utilize Azure technologies like Azure Cognitive Technologies, Azure Machine Learning, and Azure Bot Services to design, create, and deploy AI/Client based applications
• Include AI components into data workflows, engage with data scientists and data engineers
• Utilize Azure AI services to implement natural language processing (NLP) create and implement machine learning models and algorithms
• Automate the deployment and monitoring of AI models, collaborate with DevOps teams
• Use AI to automate processes such as sentiment analysis, image identification, recommendation systems, and chatbots
• Implementing machine learning pipelines and workflows
• Deploying and scaling Client models in production environments
• Automating CI/CD pipelines to account for data, code, and model changes
• Monitoring model performance and applying updates as needed
• Ensuring the security and compliance of machine learning systems
• Collaborating with data scientists to optimize models and improve performance

Skills

• Bachelor's Degree, (BA/BS) in Information Systems from a four-year college or university and 5 or more years of development experience required or equivalent combination or education and experience
• Travel up to 25%
• Total of 3-6 years of experience in managing machine learning projects end-to-end, with the last 18 months focused on MLOps
• Strong programming skills, preferably in languages like Python, Java, or Scala
• Proficiency in machine learning libraries and frameworks, such as TensorFlow, PyTorch, or scikit-learn
• Experience with containerization technologies, like Docker and Kubernetes
• Familiarity with Client model deployment tools, such as MLflow or Kubeflow
• Working experience in Azure cloud platform
• Automation of machine learning model deployment

Qualifications

Must Haves

• Bachelor's Degree, (BA/BS) in Information Systems from a four-year college or university and 5 or more years of development experience required or equivalent combination or education and experience
• Travel up to 25%
• Total of 3-6 years of experience in managing machine learning projects end-to-end, with the last 18 months focused on MLOps
• Strong programming skills, preferably in languages like Python, Java, or Scala
• Proficiency in machine learning libraries and frameworks, such as TensorFlow, PyTorch, or scikit-learn
• Experience with containerization technologies, like Docker and Kubernetes
• Familiarity with Client model deployment tools, such as MLflow or Kubeflow
• Working experience in Azure cloud platform
• Automation of machine learning model deployment

Benefits

• Medical
• Dental
• Vision