Lead AI/ML Engineer

Accountabilities: • Lead the architectural design and strategic development of high-performance AI and Machine Learning pipelines for complex enterprise initiatives.

• Define technical vision, architecture, and engineering standards for AI/ML solutions across projects.

• Provide technical leadership, mentorship, and guidance to AI/ML engineers and data scientists, promoting engineering excellence and professional growth.

• Deploy, manage, and scale pre-trained and custom AI/ML models, including LLMs, vision models, and Generative AI solutions, in production environments.

• Partner with data scientists and researchers to transform experimental models and prototypes into resilient, production-grade systems.

• Design and optimize AI/ML solutions for latency, scalability, reliability, performance, and cost efficiency.

• Integrate AI/ML platforms with AWS, GCP, and Azure environments, using Docker and Kubernetes for consistent and scalable deployments.

• Establish and improve MLOps practices covering automated testing, CI/CD, model versioning, monitoring, logging, maintenance, and operational governance.

• Build and orchestrate complex Machine Learning pipelines using platforms and tools such as Kubeflow, MLflow, and managed cloud services.

• Work with software engineering teams to integrate AI capabilities into enterprise applications and user workflows in a secure and responsible manner.

• Partner with senior leadership, product managers, solution architects, clients, and other stakeholders to align AI roadmaps with business objectives.

• Drive technical decisions and contribute to project delivery while balancing architectural quality, business requirements, and operational realities.

• Monitor developments in AI/ML research, Generative AI, data engineering, agentic systems, and MLOps to identify opportunities for innovation.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or another relevant quantitative discipline; a Ph.D. is a plus.

• 7–10 years of progressive experience in Machine Learning Engineering, AI-focused software development, or a closely related field.

• Expert knowledge of ADK and other agentic AI frameworks, with demonstrated experience implementing AI agents in production.

• Proven technical leadership experience, including mentoring engineers, influencing architectural decisions, and driving delivery across complex projects.

• Expert-level Python programming skills and strong experience with ML/AI frameworks such as TensorFlow, PyTorch, or Scikit-learn.

• Hands-on experience deploying and fine-tuning advanced pre-trained models, particularly LLMs and Generative AI technologies, in low-latency production environments.

• Extensive experience with AWS, GCP, and/or Azure, combined with strong knowledge of Docker and Kubernetes.

• Solid understanding of Data Engineering principles, ETL/ELT processes, and Git-based version control.

• Proven experience building scalable, distributed AI/ML systems and orchestrating complex Machine Learning pipelines.

• Strong knowledge of MLOps practices, including model monitoring, logging, explainability, model versioning, and CI/CD for AI assets.

• Strong understanding of production reliability, scalability, security, and responsible AI practices.

• Excellent communication, stakeholder management, and collaboration skills, with the ability to work effectively with technical and business audiences.

• Ability to translate complex AI capabilities into practical solutions that deliver measurable business value.

Benefits:

• Competitive total rewards package.

• Fully remote work from home with no daily office commute required.

• Flexible work environment designed to support work-life balance.

• Opportunity to collaborate with experienced AI, data, cloud, and engineering professionals.

• Substantial training and professional development allowance.

• Dedicated professional development days and support for training and industry certifications.

• Equipment provided for remote work, including a laptop with a choice of operating system.

• Annual budget to personalize and improve your home workspace.

• Annual wellness budget that can be used for activities such as gym memberships, fitness programs, massages, and other wellness needs.

• Generous paid vacation and sick leave.

• Paid day off for volunteering with a charity of your choice.

• Opportunity to work with advanced AI technologies and complex enterprise transformation initiatives.

• High level of technical ownership and influence over AI architecture, engineering practices, and delivery.

• Accommodation support available upon request during the selection process.

• Employment may be subject to requirements for a background check.

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