AI and Machine Learning Consultant

Overview 

In today's rapidly evolving environment, organizations need to make data-driven decisions that deliver enterprise value. Our OnX Cloud and Artificial Intelligence practitioners design, develop, and implement large-scale data ecosystems, leveraging cloud-based platforms to integrate structured and unstructured data. We utilize automation, cognitive, and science-based techniques to manage data, predict scenarios, and prescribe actions. By continuously optimizing our cloud infrastructure and providing As-a-Service offerings, we ensure ongoing insights and improvements to enhance operational efficiency. We assist clients in transforming their businesses by developing organizational intelligence programs and strategies, enabling them to stay ahead in their markets. 

Responsibilities 

As an AI and Machine Learning Consultant, you will: 

• Identify AI/ML use cases aligned with client business goals across industries like healthcare or retail. 

• Develop machine learning models using platforms like AWS SageMaker or Azure Machine Learning. 

• Implement generative AI solutions such as chatbots or recommendation engines using Vertex AI or Azure OpenAI Service. 

• Provide guidance on responsible AI practices to ensure ethical deployment of models. 

• Collaborate with stakeholders to integrate AI into existing workflows. 

Requirements 

Required: 

• Expertise in machine learning frameworks (e.g., TensorFlow, PyTorch) and cloud-based AI platforms. 

• Strong knowledge of NLP, computer vision, or predictive analytics techniques. 

• Ability to translate complex technical concepts into business value propositions. 

• Knowledge of AI ethics and responsible AI practices to ensure fair and unbiased model outcomes. 

• Experience with cloud-native analytics platforms like Azure Fabric, Azure Synapse Analytics, or Google BigQuery. 

• Strong programming skills in Python or Scala for data processing tasks. 

• Excellent problem-solving skills and the ability to troubleshoot complex technical issues. 

• Effective communication skills, written and oral. 

• Advanced understanding of data engineering principles, including data pipeline creation and data warehousing. 

• Experience with model deployment and monitoring in production environments. 

• Knowledge of AI ethics and responsible AI practices to ensure fair and unbiased model outcomes. 

• Proficiency in using version control systems like Git for collaborative code development. 

• Familiarity with Agile methodologies and experience working in Agile teams. 

• Ability to perform exploratory data analysis to uncover insights and inform model development. 

• Experience with integrating and working alongside DevOps teams to ensure smooth workflow transitions. 

Nice to have: 

• Certifications: AWS Certified Machine Learning Specialist or Azure AI Engineer Associate. 

Education 

• The ideal candidate should have a Bachelor's Degree or equivalent in a relevant field such as Business, Computer Science, Engineering, Mathematics, or a related discipline. 

Due to U.S. Government requirements applicable to foreign-owned telecommunications providers, non-US citizens may be required to submit to an extensive government agency background check which will necessitate disclosure of sensitive Personally Identifiable Information.