Senior Machine Learning Technical Client Leader

About The Company

Caylent is a cloud-native services company dedicated to empowering organizations by leveraging Amazon Web Services (AWS). Our expertise spans the full spectrum of AWS offerings, including workload migrations, modernization, cloud-native application development, DevOps, data engineering, security, and compliance. We are committed to helping our clients optimize their technology and harness the potential of their people to achieve strategic goals. As a global, fully remote organization, Caylent values a culture that celebrates diversity, fosters technological curiosity, and prioritizes the well-being of our team members across Canada, the United States, and Latin America. Our mission is to deliver innovative cloud solutions while maintaining a strong community of talented professionals who are passionate about technology and continuous learning.

About The Role

We are seeking a highly experienced Senior Machine Learning (ML) Technical Client Leader to join our team. This role combines deep hands-on expertise in machine learning with strategic advisory and consulting skills. As a key technical authority, you will lead complex client engagements, providing guidance on ML architecture, deployment, and operational best practices. Your role will involve assessing client infrastructure, data pipelines, and organizational readiness for ML initiatives, as well as shaping strategic roadmaps that align with business objectives. You will serve as a trusted advisor, influencing architecture decisions, designing high-quality proof-of-concept (POC) projects, and ensuring the successful delivery of scalable ML systems on AWS. This position offers the opportunity to work across diverse industries and challenge yourself by solving complex problems at the forefront of AI and ML innovation.

Qualifications

• 10+ years of experience in machine learning or AI, with a proven track record of leading client-facing engagements.
• Deep, current knowledge of the AWS ML and Generative AI ecosystems.
• Expertise in multiple ML domains such as traditional ML, computer vision, NLP, time series, or others.
• Proven ability to architect and govern production ML systems end-to-end, including MLOps, LLMOps, and AI operations.
• Extensive experience with foundation model adaptation techniques like fine-tuning, RLHF, inference optimization, and distributed training.
• Strong ability to operate independently in complex customer environments, navigating ambiguity and aligning stakeholders.
• AWS Certified Machine Learning – Specialty and/or AWS Certified Solutions Architect – Professional certifications preferred.
• Experience in shaping practice-level standards, reference architectures, and reusable ML accelerators.
• Deep understanding of responsible AI practices, including bias detection, fairness, and AI governance.
• Hands-on experience designing and deploying AI-driven operations workflows, including incident detection and remediation.
• Excellent communication skills, capable of translating technical trade-offs into business value for diverse audiences.

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• Exposure to multiple industry sectors and problem types in a consulting or client-facing setting.
  
  

Responsibilities

• Lead comprehensive ML assessments covering infrastructure, data pipelines, model lifecycle, and organizational readiness, providing strategic recommendations to clients.
• Collaborate with sales and solutions teams during proposal development, contributing technical expertise to define scope and deliverables.
• Serve as the senior technical authority on client projects, offering architectural guidance, ensuring quality, and providing hands-on support when necessary.
• Design and orchestrate high-quality proof-of-concept projects to demonstrate value and build client confidence.
• Advise clients on ML operations standards, including pipeline design, model management, LLMOps patterns, and production monitoring frameworks.
• Shape and influence the company's approach to winning complex technical opportunities, contributing architectural insights and credibility.
• Mentor peers through technical guidance, interviews, and contributions to accelerators, reference architectures, and thought leadership content.
• Stay current with advancements in ML, AI, and AWS ecosystems, integrating best practices into client solutions and internal standards.
• Promote responsible AI practices, ensuring models are evaluated for bias, fairness, and governance compliance in enterprise deployments.
• Design and deploy AI operations workflows, including incident detection, triage, and remediation, to enhance system reliability and business outcomes.
  
  

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Benefits

• Medical insurance coverage for employees and eligible dependents.
• 401(k) plan with company matching up to 4% and immediate vesting.
• Company-issued laptop and equipment stipend.
• Dental and vision insurance plans.
• Term disability and term life insurance coverage.
• Flexible Spending Account options.
• Annual learning and development stipend.
• Equipment and office setup stipend.
• Unlimited paid time off after a 90-day probation period.
• 10 paid holidays annually.
  
  

Equal Opportunity

Caylent is an equal opportunity employer. We are committed to creating an inclusive environment and do not discriminate against any individual based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other legally protected characteristics. We encourage applicants from diverse backgrounds to apply. If you require accommodations during the application process due to a disability, please contact us at hr@caylent.com.