ML Solutions Architect Jobs

Provectus

Location:
Colombia, Medellín ▼
Bogotá
Cali
Barranquilla
Bucaramanga

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

As an ML Solutions Architect, you'll be the technical bridge between clients and delivery teams. You'll lead pre-sales technical discussions, design ML architectures that solve business problems, and ensure solutions are feasible, scalable, and aligned with client needs. This is a highly client-facing role requiring both deep technical expertise and strong communication skills.

Job Responsibility:

Lead technical discovery sessions with prospective clients
Understand client business problems and translate them into ML solutions
Design end-to-end ML architectures and technical proposals
Create compelling technical presentations and demonstrations
Estimate project scope, timelines, cost, and resource requirements
Support General Managers in winning new business
Serve as the primary technical point of contact for clients
Manage technical stakeholder expectations
Present technical solutions to both technical and non-technical audiences
Navigate complex organizational dynamics and conflicting priorities
Ensure client satisfaction throughout the project lifecycle
Build long-term trusted advisor relationships
Collaborate with delivery teams to ensure smooth handoff
Provide technical guidance during project execution
Contribute to the development of reusable solution patterns
Share learnings and best practices with ML practice
Mentor engineers on client communication and solution design

Requirements:

Ability to architect end-to-end ML systems for diverse business problems
Deep understanding of the full ML lifecycle from data to deployment
Experience designing scalable, production-grade ML architectures
Ability to evaluate technical approaches (cost, performance, complexity)
Quickly assess if ML is an appropriate solution for a problem
Experience across various ML applications (RAG, Computer Vision, Time Series, Recommendation, etc.)
Strong experience in architecting LLM-based applications
Foundation in traditional ML algorithms and when to use them
Understanding of neural network architectures and applications
Knowledge of production ML infrastructure and DevOps practices
Advanced knowledge of AWS ML and data services
Advanced knowledge of GCP ML and data services
Understanding of Azure, GCP alternatives
Experience with Lambda, API Gateway, etc.
Ability to design cost-effective solutions
Understanding of data security, privacy, and compliance
Understanding of ETL/ELT patterns and tools
Knowledge of databases, data lakes, and warehouses
Understanding of data validation and monitoring
Ability to design for different data processing needs

Additional Information:

Job Posted:
December 11, 2025

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ML Solutions Architect