Model Deployment

Voya Financial

Full-time · $192,580 – $240,720

Lead the design and delivery of production-grade AI systems at scale, owning major technical components and influencing architectural decisions across the organization. This role suits experienced engineers ready to mentor others and operate with high autonomy while navigating the constraints of a regulated financial services environment.

Listed on Voya Financial’s careers site · Apply there ↗

Shield AI

Full-time · Washington, DC · $163,200 – $244,800

This role involves building and deploying machine learning models for autonomous systems, focusing on computer vision and vision-language capabilities. It suits engineers who want to move cutting-edge AI research into production systems while working cross-functionally with researchers and autonomy teams.

Listed on Shield AI’s careers site · Apply there ↗

Palantir

Full-time · Seattle, WA · $145,000 – $200,000

This role focuses on building and deploying AI models and agents optimized for resource-constrained tactical hardware in defense applications, requiring expertise in LLMs, edge computing, and systems integration. It suits engineers with experience in AI systems, hardware optimization, and a background working on specialized deployments.

Listed on Palantir’s careers site · Apply there ↗

MovieMagic

Tempe, AZ

Entertainment Partners is hiring a senior AI engineer to develop and deploy machine learning models and AI systems for its entertainment technology products. This role suits someone with strong PyTorch and transformer expertise who can move models from research through production while maintaining software engineering rigor.

Listed on MovieMagic’s careers site · Apply there ↗

Torc Robotics

Full-time · Remote - US · $160,800 – $193,000

This role involves building machine learning infrastructure and AI tooling at an autonomous trucking company, with significant responsibility for translating complex business problems into production ML systems. It suits experienced engineers comfortable with ambiguity who can work across teams to implement cutting-edge technology at scale.

Listed on Torc Robotics’s careers site · Apply there ↗

Pendo

New York, NY · $300,000 – $325,000

Staff-level role building AI-native products and systems within a product intelligence platform. Suited for experienced engineers who combine deep LLM expertise with product thinking, thrive in ambiguity, and can drive technical decisions and cross-team influence at scale.

Listed on Pendo’s careers site · Apply there ↗

Metropolis Technologies

Full-time · Seattle, WA · $200,000 – $250,000

Metropolis seeks a hands-on senior manager to lead machine learning infrastructure and data engineering teams building production AI systems for a computer vision and parking technology platform. The role requires balancing strategic oversight of 4 teams with deep technical involvement in MLOps, data pipelines, and agentic AI deployment.

Listed on Metropolis Technologies’s careers site · Apply there ↗

Agility Robotics

Full-time · Fremont, CA · $207,000 – $323,000

A staff-level machine learning engineer role focused on building perception systems for deployed humanoid robots operating in warehouses and manufacturing. This position suits engineers with deep expertise in object detection and tracking who want to own the full technical architecture of computer vision systems deployed on real robots at scale.

Listed on Agility Robotics’s careers site · Apply there ↗

CharacterAI

Redwood City, CA · $150,000 – $300,000 · Remote

This role focuses on building scalable backend systems and applying machine learning to detect and prevent safety risks on an AI platform where users interact with characters. It suits engineers with deep expertise in distributed systems and ML who want to lead technical strategy on emerging AI safety challenges.

Listed on CharacterAI’s careers site · Apply there ↗

Pendo

Full-time · New York, NY · $250,000 – $275,000

A senior engineer role building AI-native products from prototype to production, designing RAG pipelines, agentic workflows, and LLM-powered features that ship to real customers. This suits experienced builders who thrive in ambiguous spaces, make principled technical choices under uncertainty, and partner closely with product to define what should be built.

Listed on Pendo’s careers site · Apply there ↗