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ML Solutions Architect (with GenAI)

1 month ago
Colombia
Full-time
Senior
AI (Artificial Intelligence)
DevOps and Infrastructure
API Gateway AWS Azure Computer Vision Deep Learning GCP LLM MLOps Neural Networks Serverless
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Provectus

Provectus

Provectus provides consulting services in artificial intelligence and machine learning, assisting businesses in integrating AI solutions to meet their unique objectives and enhance their operational capabilities across various industries.

Professional Services
251-1K
Founded 2010
View All Jobs 2

Description

  • Lead technical discovery and pre-sales sessions with prospective clients to understand business problems and translate them into ML solutions.
  • Design end-to-end, production-grade ML architectures and prepare technical proposals, estimates, timelines, costs, and resource plans.
  • Create and deliver technical presentations, demonstrations, and proposals for both technical and non-technical audiences.
  • Serve as the primary technical point of contact for clients, manage stakeholder expectations, and ensure client satisfaction throughout the project lifecycle.
  • Assess feasibility and trade-offs of ML approaches (cost, performance, complexity) and decide whether ML is an appropriate solution.
  • Collaborate with delivery teams to ensure smooth handoff and provide technical guidance during project execution.
  • Contribute reusable solution patterns, share learnings and best practices across the ML practice, and document architecture decisions.
  • Mentor engineers on client communication, solution design, and technical delivery best practices.
  • Support General Managers and commercial teams in winning new business by providing technical leadership and proposals.

Requirements

  • Proven ability to architect end-to-end ML systems and design scalable, production-grade ML architectures.
  • Deep understanding of the full ML lifecycle from data ingestion through model deployment and monitoring.
  • Experience across multiple ML domains (e.g., RAG/LLM applications, computer vision, time series, recommendations).
  • Strong experience architecting LLM-based applications and practical knowledge of classical ML and deep learning approaches.
  • Familiarity with MLOps, production ML infrastructure, DevOps practices, and model monitoring/validation.
  • Advanced knowledge of cloud ML and data services on AWS and GCP, with multi-cloud awareness (including Azure) and serverless experience (e.g., Lambda, API Gateway).
  • Ability to perform trade-off analysis for cost, performance, and complexity, and design cost-optimized solutions.
  • Understanding of data architecture including ETL/ELT patterns, data storage options (databases, data lakes, warehouses), data quality, and real-time vs batch processing.
  • Knowledge of data security, privacy, and compliance considerations for ML solutions.
  • Strong client-facing communication skills, experience with pre-sales technical leadership, stakeholder management, and mentoring teams.

Interested in this position?

Apply directly on the company website

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