3 months ago
Remote, BrazilStaff+
Responsibilities
- Define the technical vision, strategy, and architecture for enterprise AI and machine learning solutions.
- Lead the architectural design and strategic development of high-performance AI/ML pipelines.
- Provide technical leadership, mentorship, and guidance to AI/ML engineers and data scientists.
- Deploy, manage, scale, and fine-tune pre-trained and custom AI models in production environments.
- Operationalize research and prototype models into resilient, production-grade AI systems.
- Optimize model performance, latency, and cost across cloud and edge deployment targets.
- Integrate AI/ML solutions with AWS, GCP, and Azure using Docker and Kubernetes.
- Implement MLOps practices including model testing, CI/CD, versioning, monitoring, logging, explainability, and maintenance.
- Partner with senior leadership, product managers, clients, solution architects, data scientists, and business stakeholders on AI roadmaps and delivery.
- Ensure ethical and seamless integration of AI capabilities into larger software applications and user workflows.
Requirements
- Bachelor’s or master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related quantitative field; a Ph.D. is a plus.
- 7–10 years of progressive experience in machine learning engineering, software development with an ML/AI focus, or a related role.
- Expert knowledge of ADK and other agentic frameworks, with deep experience implementing agents in production.
- Proven technical leadership experience, including mentoring engineers, driving architectural decisions, and managing project delivery.
- Expert Python programming skills and proficiency with TensorFlow, PyTorch, or Scikit-learn.
- Hands-on experience deploying and fine-tuning LLMs or comparable generative AI technologies in low-latency production environments.
- Extensive experience with AWS, GCP, Azure, Docker, and Kubernetes.
- Proficiency in data engineering principles, ETL/ELT processes, and Git.
- Experience orchestrating complex machine learning pipelines with Kubeflow, MLflow, or managed cloud services.
- Experience building and optimizing scalable, distributed AI/ML systems.
- Deep familiarity with MLOps best practices and CI/CD pipelines for AI assets.
- Strong communication and teamwork skills across technical, product, client, and business stakeholder groups.
Benefits
- Fully remote work from home with no daily office travel requirement and a stable internet connection.
- Competitive total rewards package.
- Training allowance, professional development days, training opportunities, and certification support.
- Company-provided work-from-home equipment, including a laptop with a choice of operating system.
- Annual budget for personalizing the home workspace.
- Annual wellness budget for items such as gym memberships, massages, and fitness activities.
- Paid vacation and sick days.
- Paid day off to volunteer for a preferred charity.
- Opportunity to blog during work hours and volunteer.
Tech Stack
AWSAzureDockerGitGoogle CloudGoogle Cloud PlatformKubernetesMLflowPythonPyTorchscikit-learnSnowflakeTensorFlow
Categories
About Pythian
Pythian is an Ottawa-based IT services firm providing data, analytics, AI, and cloud consulting plus 24/7 managed database and infrastructure operations for mid-market and enterprise clients. Founded in 1997 and privately held, it is part of Mill Point Capital’s portfolio; its engineers support Oracle, SQL Server, MySQL, NoSQL, and DevOps across multi-cloud and on-premises environments. Its business model combines project-based consulting, implementations, and recurring managed services.