AI/ML Solutions Architect

This is a fully remote position, open to applicants in Colombia.

📋 Description

• Facilitate technical discovery sessions with potential clients.

• Comprehend client business challenges and convert them into machine learning solutions.

• Develop comprehensive end-to-end machine learning architectures and technical proposals.

• Craft engaging technical presentations and demonstrations.

• Estimate project scope, timelines, costs, and resource needs.

• Assist General Managers in acquiring new business opportunities.

• Act as the main technical liaison for clients.

• Manage expectations of technical stakeholders.

• Present technical solutions to both technical and non-technical audiences.

• Navigate complex organizational dynamics and manage conflicting priorities.

• Ensure client satisfaction throughout the entirety of the project lifecycle.

• Establish long-term trusted advisor relationships.

• Collaborate with delivery teams to ensure a seamless handoff.

• Provide technical leadership during project execution.

• Contribute to the creation of reusable solution patterns.

• Share insights and best practices within the machine learning practice.

• Coach engineers on client communication and solution design.

⛳️ Requirements

• Solution Design: Proficient in architecting end-to-end machine learning systems for a variety of business challenges.

• ML Lifecycle: Extensive knowledge of the complete machine learning lifecycle from data acquisition to deployment.

• System Design: Proven experience in designing scalable, production-ready machine learning architectures.

• Trade-off Analysis: Skilled in evaluating technical methods based on cost, performance, and complexity.

• Feasibility Assessment: Ability to swiftly determine the appropriateness of machine learning as a solution for specific problems.

• Multiple ML Domains: Experience with a range of machine learning applications, including RAG, Computer Vision, Time Series, Recommendations, etc.

• LLM Solutions: Significant experience in architecting applications based on Large Language Models.

• Classical ML: Solid understanding of traditional machine learning algorithms and their appropriate applications.

• Deep Learning: Knowledge of neural network architectures and their applications.

• MLOps: Familiarity with production machine learning infrastructure and DevOps methodologies.

• AWS Expertise: Advanced understanding of AWS machine learning and data services.

• GCP Expertise: Advanced understanding of GCP machine learning and data services.

• Multi-Cloud Awareness: Knowledge of Azure and GCP alternatives.

• Serverless Architectures: Experience with Lambda, API Gateway, and similar technologies.

• Cost Optimization: Capability to design solutions that are cost-effective.

• Security and Compliance: Knowledge of data security, privacy regulations, and compliance standards.

• Data Pipelines: Understanding of ETL/ELT patterns and associated tools.

• Data Storage: Familiarity with databases, data lakes, and data warehouses.

• Data Quality: Knowledge of data validation and monitoring practices.

• Real-time vs Batch: Ability to design solutions catering to diverse data processing requirements.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible work hours and remote work options.

• Professional development and training opportunities.

• Collaborative and inclusive work environment.