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Full Time Horizon Robotics Jobs (NOW HIRING)

UPMC Senior Communities

Pharmacist - Nights

Erie, PA · On-site

$51.03 - $76.98/hr

Pharmacist - Night Position (Full-Time) UPMC Hamot | Erie, PA UPMC Hamot is seeking a full-time ... Full pharmacy automation (XR2 robots, medication carousels, ADCs, and controlled substance ...

Arc Boat Company

Director, Defense

Torrance, CA

This is a full-time, on-site role at our Los Angeles headquarters, reporting to our CTO. You'll ... Familiarity with autonomy, robotics, and maritime systems * Enthusiasm for boating and clean energy ...

Arc Boat Company

Director, Defense

Torrance, CA · On-site

This is a full-time, on-site role at our Los Angeles headquarters, reporting to our CTO. You'll ... Familiarity with autonomy, robotics, and maritime systems * Enthusiasm for boating and clean energy ...

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Full Time Horizon Robotics information

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How much do full time horizon robotics jobs pay per year?

As of Sep 11, 2026, the average yearly pay for full time horizon robotics in the United States is $96,000.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $102,000.00 per year, depending on experience, location, and employer.

What is the difference between Full Time Horizon Robotics vs Full Time AI Software Engineer?

AspectFull Time Horizon RoboticsFull Time AI Software Engineer
Required CredentialsBachelor's or higher in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and AI hardwareBachelor's or higher in Computer Science, Software Engineering, or related fields; proficiency in AI algorithms and software development
Work EnvironmentEmbedded systems, hardware integration, AI chip developmentSoftware development, AI model implementation, cloud and server environments
Industry UsageAutonomous vehicles, robotics, AI hardware companiesTech companies, AI startups, software firms

Full Time Horizon Robotics roles focus on hardware-software integration for AI chips in autonomous systems, while Full Time AI Software Engineers primarily develop AI algorithms and software applications. Both roles require strong technical skills but differ in their focus on hardware versus software development within the AI industry.

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What are the most commonly searched types of Horizon Robotics jobs?

The most popular types of Horizon Robotics jobs are:

What job categories do people searching Full Time Horizon Robotics jobs look for?

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Full Time Horizon Robotics jobs near you
Infographic showing various Full Time Horizon Robotics job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 90% Full Time, 5% Part Time, 3% Contract, and 1% Nights. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $96,000 per year, or $46.2 per hour.

Member of Technical Staff, Mid-training

San Jose, CA • On-site

Hark
See more jobs at Harkexternal

$180K - $450K/yr

Full-time

Re-posted 26 days ago

Job description

About Hark
Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory.
We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world.
To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems.
About the Role
We are looking for a Member of Technical Staff - Mid-Training to lead the development of training strategies that bridge pre-training and post-training, shaping how models acquire reasoning, planning, and tool-use capabilities at scale.
This role sits at the core of model capability development-defining how data, algorithms, and systems interact to unlock the next frontier of agent behavior.
Responsibilities
  • Design and implement mid-training strategies to improve agent capabilities such as reasoning, planning, tool use, and long-horizon decision-making.
  • Scale synthetic data generation pipelines (e.g., coding, agent trajectories, multimodal data) and optimize data mixtures to improve downstream RL performance.
  • Build and optimize distributed training pipelines for large models, ensuring efficiency, stability, and scalability across GPU clusters.
  • Develop and iterate on evaluation frameworks to measure model capability (e.g., task success, reasoning quality, tool use accuracy) and guide training improvements.
  • Conduct rigorous experimentation and ablations to understand training dynamics, scaling behavior, and bottlenecks.
  • Collaborate cross-functionally with pre-training, post-training, and product teams to align model development with real-world agent use cases.
  • Drive technical innovation in areas such as long-context learning, data distillation, and training efficiency, while contributing to the overall model roadmap.

Requirements
  • Strong background in machine learning, with hands-on experience training or fine-tuning large models - LLMs, multimodal, or equivalent systems.
  • Deep understanding of reinforcement learning: policy optimization, reward design, exploration, and the interplay between environment design and agent behavior.
  • Experience building or working within simulation or execution environments (e.g., code interpreters, sandboxed execution, game environments, robotics simulators).
  • Proven ability to design and execute rigorous experiments, with strong intuition for diagnosing training failures and scaling bottlenecks.
  • Proficiency in Python and PyTorch; comfort working across research and systems code.
  • Ability to work in a fast-moving, research-forward environment where the right approach is often unknown at the outset.

We expect strong candidates to come from a range of backgrounds - RL research, robotics, competitive programming systems, compilers, formal methods, or large-scale ML - rather than post-training specifically. The field is new enough that directly relevant experience is rare; what matters is depth, rigor, and transferability.
Bonus Qualifications
  • Experience with mid-training, post-training, or agent-focused model development or coding LLM training.
  • Familiarity with synthetic data generation, trajectory-based training, or coding/model distillation pipelines.
  • Experience training or scaling large models (100B+ parameters or equivalent systems).
  • Background in reinforcement learning, decision-making systems, or agent frameworks.
  • Contributions to open-source ML systems or publications at top conferences (ICML, NeurIPS, ICLR, ACL, etc.).
  • Experience optimizing distributed training systems (GPU utilization, memory efficiency, communication).

Compensation
The US base salary range for this full-time position is between $180,000 - $450,000 annually.
The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components and benefits depending on the specific role. This information will be shared if an employment offer is extended.

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