Research Engineer

Acceler8 Talent; Mountain View (CA); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Acceler8 Talent is seeking a Research Engineer to help an AI and robotics startup build an AI-powered observability platform for critical infrastructure in Mountain View, CA.

You will design and implement multimodal AI systems that combine language, vision, and agentic reasoning, scale reasoning across data from drones and robots, and enable real-world deployments.

Qualifications

• Experience with vision-language models or multimodal reasoning.
• Strong background in ML, deep learning, or applied AI research.
• Production-grade software engineering experience.

Responsibilities

• Build multimodal AI systems combining language models, vision models, and agentic reasoning
• Develop VLMs and multimodal agents capable of understanding, analyzing, and acting on complex real-world data
• Design systems that allow users to interact naturally with fleets of autonomous robots
• Work on large-scale reasoning systems that analyze historical incidents, identify faults, and recommend corrective actions
• Build infrastructure for grounding language models in visual observations from drones and robotic platforms
• Develop retrieval, memory, and decision-making systems for mission-critical environments
• Collaborate closely with robotics and autonomy engineers to bridge perception, reasoning, and execution
• Help shape the future architecture of a rapidly evolving AI platform operating in the physical world

Skills

VLMs

Multimodal AI

LLMs

Production-grade ML

Job description

Research Engineer (VLM / Multimodal AI)

Mountain View, CA

I am seeking a Research Engineer to join a venture-backed AI and robotics startup building an AI-powered observability platform for critical infrastructure. This is an opportunity to work on cutting-edge multimodal AI systems that combine language, vision, agentic reasoning, and robotics to monitor and manage some of the world's largest physical environments, including data centers, solar farms, wind farms, and oil refineries.

The company has already deployed its technology with customers, recently secured FAA approval for autonomous drone operations, and is founded by former Google and Meta robotics engineers with multiple successful exits valued at over $450M combined.

What You'll Do:

• Build multimodal AI systems combining language models, vision models, and agentic reasoning
• Develop VLMs and multimodal agents capable of understanding, analyzing, and acting on complex real-world data
• Design systems that allow users to interact naturally with fleets of autonomous robots
• Work on large-scale reasoning systems that analyze historical incidents, identify faults, and recommend corrective actions
• Build infrastructure for grounding language models in visual observations from drones and robotic platforms
• Develop retrieval, memory, and decision-making systems for mission-critical environments
• Collaborate closely with robotics and autonomy engineers to bridge perception, reasoning, and execution
• Help shape the future architecture of a rapidly evolving AI platform operating in the physical world

What We're Looking For:

• Experience working with Vision Language Models (VLMs), multimodal foundation models, or Vision Language Action (VLA) systems
• Strong background in machine learning, deep learning, or applied AI research
• Experience with LLMs, agentic systems, retrieval, or multimodal reasoning
• Exposure to computer vision, perception, robotics, autonomy, or embodied AI is highly desirable
• Strong software engineering skills with the ability to build production-grade AI systems
• Experience taking research concepts into real-world applications
• Ability to thrive in highly autonomous, fast-moving startup environments

This role sits at the intersection of some of the most exciting areas in AI today: multimodal models, agentic systems, robotics, and real-world deployment.

You’ll help build an intelligent platform capable of identifying faults across infrastructure the size of small cities, analyzing historical and live operational data, coordinating robotic inspections, and guiding human operators towards the fastest and most effective resolution.