This role exists because high-impact AI delivery often requires engineers embedded with users to rapidly discover the right AI approach, prove value beyond simple baselines, and then harden and deliver AI capabilities into production pathways.
Partner with technical sales teams as a subject matter expert in Generative AI to differentiate Google Cloud to customers, develop solutions, and troubleshoot technical issues.
Locations (4)
São Paulo, São Paulo, Brazil
Santiago, Santiago, Chile
Bogotá, Bogota, Colombia
Mexico City, CDMX, Mexico
Responsibilities
Partner with the business team to identify and qualify AI business opportunities
Act as the primary technical advisor for AI adoption
Support bid responses, product and solution briefings
Demonstrate and prototype integrations in customer and partner environments
Computer Vision & VLM Engineer – Founding Team, Multimodal AI
MaxIT Consulting - Max Corporate Group · Posted Nov 12, 2026
Design, implement, train, adapt, and evaluate reasoning and cognition models for unmanned autonomous platforms.
Compensation
Pay within range listed + Bonus + Benefits + Equity
Responsibilities
Design, implement, train, adapt, and evaluate reasoning and cognition models for unmanned autonomous platforms.
Make and validate tradeoffs among foundation-model approaches, including vision-language models (VLMs) and vision-language-action models (VLAs), specialized deep-learning models, and traditional AI/ML methods.
Develop capabilities for interpreting context, reasoning over time, coordinating among agents, and adapting to incomplete or changing information.
Build reproducible training and adaptation workflows using appropriate combinations of self-supervised learning, supervised fine-tuning, imitation learning, reinforcement learning, and distillation.
Define data requirements, training objectives, benchmarks, and evaluation methods that support meaningful comparisons among model approaches.
Requirements
BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience
Nice to have: MS or PhD in Computer Science, Electrical Engineering, or similar degree
Nice to have: Optimising and deploying ML models to resource-constrained hardware platforms
Build software that enables SI agents and multimodal models to interact with real-world equipment through an existing hardware integration stack.
Compensation
$121,830 - $185,544 Annually
$121,830 - $154,500 Annually for the SES.1 level
$146,340 - $185,544 Annually for the SES.3 level
Responsibilities
Implement agent-facing tool definitions and task workflows that use documented equipment interfaces and platform services.
Develop multimodal perception and decision-support workflows using camera, telemetry, and process data.
Improve prompt logic, tool use, evaluation methods, and workflow reliability for physical-world SI applications.
Translate real-world operational tasks into practical SI-assisted workflows that are usable, testable, and maintainable.
Work with embedded, platform, and deployment engineers in a controlled environment to define safe action boundaries, human- or system-mediated approval points, and fallback behaviors using established external safety and security systems.
Requirements
Bachelor's degree in computer science, software engineering, robotics, or related field
Customer Engineer, Generative AI, LATAMNewGoogle · São Paulo, Brazil+3 more
Computer Vision & VLM Engineer – Founding Team, Multimodal AIMaxIT Consulting - Max Corporate Group · Burlingame, US+1 more
Staff Engineer, Hivemind Reasoningf7d8749a-72d6-407c-bf98-292ea630c73a · San Mateo, US