AI/ML Engineer

Job Profile: AI/ML Engineer

Job Description: As an AI/ML Engineer in our Intelligent Process Automation Center of Excellence, you will be at the forefront of developing and managing the AI infrastructure that powers our business. Your role will involve building AI models from scratch, automating AI infrastructure, and collaborating with cross-functional teams to drive AI adoption and best practices. This position requires a professional with a deep understanding of AI and machine learning, combined with strong programming and data analysis skills.

Responsibilities:

AI Development and Infrastructure Management:
• Create and manage the AI development and production infrastructure.
• Automate AI infrastructures to support the data science team and streamline workflows.
• Ensure the AI infrastructure is scalable, efficient, and reliable.
Statistical Analysis and Decision-Making:
• Conduct statistical analysis and interpret results to guide and optimize organizational decision-making.
• Use data-driven insights to inform business strategies and improve operational efficiencies.
Model Building and Implementation:
• Build AI models from scratch, leveraging advanced machine learning techniques and frameworks.
• Transform machine learning models into APIs that can be integrated with other applications.
• Assist product managers and stakeholders with the analysis and implementation of AI solutions.
Collaboration and Best Practices:
• Collaborate across teams, including data scientists, data engineers, and software developers, to ensure successful AI adoption.
• Promote best practices in AI and machine learning within the organization.
• Provide technical guidance and support to team members and stakeholders.
Required Experience and Skills:
• Minimum of 3+ years of industry experience in AI, machine learning, or data science roles.
• Proficiency in programming languages such as Python, R, or Java.
• Strong understanding of machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and statistical modeling techniques.
• Experience with data preprocessing, feature engineering, and model evaluation.
• Familiarity with cloud-based ML platforms and services (e.g., AWS SageMaker, Google AI Platform, Azure ML).
• Experience in building and deploying machine learning models and APIs.
• Excellent problem-solving skills and the ability to write clean, efficient, and scalable code.
• Strong communication skills for presenting technical information to various audiences.
Minimum Qualifications:
• Bachelor’s or advanced degree in Computer Science, Data Science, AI, Machine Learning, or a related field.
• Minimum of 3+ years of relevant industry experience in AI/ML or data science roles.
Preferred Qualifications:
• Advanced degree (Master’s or Ph.D.) in a related field.
• Experience with MLOps frameworks and tools for model deployment, monitoring, and management.
• Proven success in deploying and scaling AI and ML solutions in large organizations.
• Experience with Generative AI techniques and applications.
Company Values and Culture:
• Commitment to innovation and continuous improvement.
• Emphasis on collaboration and cross-functional teamwork.
• Focus on diversity, equity, and inclusion in all aspects of the workplace.