SUMMARY

We are seeking a highly skilled and motivated Sr. AI/ML Engineer with a proven track record in designing and implementing AI solutions. The ideal candidate will have extensive experience in developing AI applications using Python libraries and popular AI frameworks, as well as proven track record and hands-on experience in delivering solutions leveraging AWS AI services. You will work collaboratively with cross-functional teams to architect, design, and deploy innovative AI solutions that drive business value and meet specific analytics requirements. Additionally, you will play a key role in mentoring team members and junior resources to foster their growth and development in the AI/ML domain.
Responsibilities:

REQUIRED QUALIFICATIONS:

• 3-5+ years of proven experience as a Sr. AI/ML Engineer or similar role, with a strong portfolio of AI solutions.
• 3-5+ years of machine learning experience with various regression, classification, and outlier detection models using structured and unstructured data.
• 3-5+ years of demonstrable proficiency in Python programming and experience with popular AI/ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Keras).
• 3+ years of hands-on experience with AWS AI services, particularly SageMaker, Bedrock and familiarity with other AWS services (e.g., S3, Lambda, EC2).
• 3+ years of experience in Python for data skills and knowledge of the Python ecosystem for AI tools.
• Strong understanding of machine learning algorithms, data structures, and software engineering principles.
• Excellent problem-solving skills and the ability to work independently and collaboratively in a fast-paced environment.
• Strong communication skills, experimentation mindset with the ability to explain complex technical concepts to non-technical stakeholders.
  Compensation:
  The proposed salary range for this role is $* to $** USD. The salary range provided is a good faith estimate representative of all experience levels. Karsun considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate’s work experience, location, education/training, and key skills

• Collaborate with business stakeholders to determine precise analytics requirements and translate them into scalable and effective AI solutions.
• Architect, design, and implement machine learning and agentic AI applications using Python and relevant libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Leverage AWS AI services (such as SageMaker, Bedrock, Comprehend, and Lex) to build robust and efficient AI solutions.
• Design & develop multi agent workflows leveraging context engineering best practices, Tools and MCP protocols.
• Collaborate with technical teams and architects to provide functional inputs for system design and implementation, ensuring alignment with business goals.
• Work closely with Solution Architects, Dev Leads, data SMEs and data engineers to establish repeatable data preparation processes in line with MLOps principles.
• Guide domain/business data scientists in selecting appropriate analytics models, algorithms, and recipes for various use cases.
• Conduct data preprocessing, feature engineering, and model evaluation to ensure high-quality outputs.
• Monitor and optimize models as systems evolve to maintain their relevancy and performance.
• Evaluate and optimize agentic AI solutions to ensure relevancy and lower TCO.
• Implement best practices for model training, validation, and deployment, including version control and CI/CD, MLOps pipelines.
• Mentor and support team members and junior resources, providing guidance on best practices, tools, and methodologies in AI/ML.
• Stay up to date with the latest advancements in AI/ML technologies and AWS services and apply this knowledge to improve existing systems and processes.
  Qualifications and Education: