Senior AI Engineer
Sezzle
ApacheAWSCloudDockerGoGrafanaKafkaKubernetesPrometheusPythonSparkSQL
AI Architect
Lean Tech
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇨🇴 Colombia
Visit company websiteJob Level
SeniorLead
Tech Stack
AWSAzureCloudGoogle Cloud PlatformKafkaKubernetesNoSQLPythonPyTorchScikit-LearnSparkSQLTensorflow
About the role
- Lead the architectural design, development, and deployment of scalable AI and machine learning systems, ensuring solutions align with business objectives and integrate seamlessly with existing infrastructure.
- Provide strategic technical leadership and mentorship to AI/ML development teams, defining architectural best practices, coding standards, and ensuring successful project delivery.
- Translate complex business requirements into robust AI solutions, selecting appropriate architectural patterns, machine learning algorithms, and deep learning models using advanced Python frameworks such as TensorFlow, PyTorch, and scikit-learn.
- Drive the selection and implementation of suitable cloud-based AI/ML services, primarily leveraging Azure Machine Learning, and ensure adherence to cloud-specific security architectures and best practices.
- Oversee the design and management of advanced data pipelines, with a focus on batch processing using tools including Spark, Azure Data Factory (ADF), Fabric, Databricks, and orchestrate end-to-end data workflows via AKS and other related technologies.
- Direct the development, deployment, and monitoring of custom machine learning models, employing advanced techniques such as transfer learning where appropriate to address business challenges.
- Design and oversee robust MLOps pipelines, including CI/CD processes, model versioning, automated retraining, model monitoring, and governance, using tools such as MLflow and Kubeflow when applicable.
- Evaluate the technical feasibility of new AI initiatives, identify potential risks, and develop effective mitigation strategies throughout the AI development lifecycle.
- Collaborate closely with product managers, stakeholders, and data scientists to define and execute long-term AI roadmaps that support organizational strategy and continuous innovation.
- Maintain the highest standards of data engineering by leading data modeling activities and managing SQL/NoSQL databases and big data technologies such as Kafka to ensure data integrity and scalability.
- Foster an environment of technical excellence by sharing expertise in software development, data analytics, and MLOps, and by communicating complex concepts clearly to technical and non-technical audiences.
Requirements
- Minimum 8 years of experience in software development, including at least 4-5 years in AI/ML-focused roles or leading AI projects.
- Expertise in designing and building scalable, production-grade AI/ML architectures and leading end-to-end development processes.
- Advanced proficiency in Python for data analytics, machine learning, and AI development, including mastery of libraries such as TensorFlow, PyTorch, and scikit-learn.
- Strong experience with deep learning architectures and a comprehensive understanding of machine learning algorithms and the full AI development lifecycle.
- Hands-on experience in developing custom machine learning models, including techniques such as transfer learning.
- Demonstrated ability to design, build, and manage complex data pipelines, with advanced knowledge of batch processing, Azure Data Factory (ADF), Fabric, and Databricks.
- Extensive experience with big data technologies, such as Spark and Kafka, and advanced data modeling capabilities.
- Advanced skills in working with SQL and NoSQL databases to support scalable AI solutions.
- Significant hands-on experience with at least one major cloud platform (AWS, Azure, or GCP), including advanced use of cloud AI/ML services and Azure Machine Learning.
- Experience in architecting and implementing cloud-specific security solutions, with a focus on Azure environments.
- Ability to design, build, and maintain robust MLOps pipelines for CI/CD, model deployment, monitoring, and governance, including practical experience with tools such as MLflow, Kubeflow, Azure Data Factory, and Azure Kubernetes Service (AKS).
- Exceptional leadership and communication skills, with proven ability to mentor teams, influence stakeholders, and clearly articulate complex technical concepts to diverse audiences.
Benefits
- Professional development opportunities with international customers
- Collaborative work environment
- Career path and mentorship programs
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
AI architecturemachine learningdeep learningPythontransfer learningdata pipelinesbatch processingdata modelingMLOpscloud AI/ML services
Soft skills
leadershipmentorshipcommunicationstrategic thinkingcollaborationproblem-solvinginfluencetechnical excellencestakeholder engagementclarity in complex concepts