Data/ ML Solution Architect
New
Medellín, Antioquia / Bogotá, Capital District / Cali, Valle del CaucaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 7+ years
- Required Skills
- AWSDockerPythonGCPJavaKubernetesMachine LearningTypeScriptAzureData engineeringMicroservicesMLOps
Requirements
- 7+ years of experience in solutions architecture, with a strong focus on Big Data and cloud platforms (AWS, GCP, Azure).
- Excellent communication and problem-solving skills.
- Technical sales or pre-sales experience with cloud and big data, and ML solutions.
- Strong leadership and team collaboration abilities.
- Proficiency in data engineering and analytics, designing data pipelines and architectures.
- Strong understanding of AI/ML concepts and experience integrating AI/ML components.
- Proven experience with data lakes, data warehouses, and real-time data analytics.
- Proven experience with microservice architecture and containerized deployment options.
- Hands-on experience with Kubernetes, Docker, and containerized applications.
- Proficiency in backend-related languages: TS, Java, Python, and others.
- Solid understanding of machine learning and MLOps tools (PyTorch, SageMaker, MLFlow).
- Familiarity with agile methodologies.
Responsibilities
- Lead the design and implementation of data and AI/ML architecture solutions across cloud and on-premise platforms.
- Lead complex customer engagements, providing strategic technical vision and aligning solutions with customer business goals.
- Build and maintain strong relationships with key customer stakeholders, acting as a trusted technical advisor.
- Lead technical workshops, training sessions, and presentations.
- Define and execute data lifecycle processes: ingestion, storage, processing, and visualization.
- Ensure solutions adhere to security, compliance, and architecture frameworks.
- Lead cross-functional teams, providing mentorship and guidance to technical talent.
- Design and execute proofs of concept for emerging technologies like Generative AI, Machine Learning.
- Drive backend/ML services best practices for scalable and maintainable solutions.
- Oversee data governance and data quality processes across platforms.
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