---
title: 'Senior Autonomy Controls Engineer – Learning-Based Control at Teleo'
canonical: 'https://feeny.ai/job/senior-autonomy-controls-engineer-learning-based-control-teleo-palo-alto-tn45bzebp4qe'
type: 'job'
last_seen: '2026-09-09'
---

# Senior Autonomy Controls Engineer – Learning-Based Control at Teleo

- **Company:** Teleo
- **Location:** Palo Alto, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-02-13
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.lever.co/teleo/26c8c2c3-37df-4db0-8dc6-ee95953bc422

## Job description

Teleo, a Havoc company, is a robotics company that transforms construction heavy equipment, including loaders, dozers, excavators, and trucks, into autonomous robots for commercial and defense applications. Our technology enables a single operator to supervise and control multiple machines simultaneously, delivering significant productivity gains while improving operator safety and comfort. Teleo was founded by a team of experienced technology leaders who previously led the development of Lyft's Self-Driving Car program and Google Street View. Teleo recently announced its merger with Havoc AI, a fast-growing defense technology company developing coordinated fleets of autonomous maritime vessels. This is a unique opportunity to join a team building technology with real-world impact. You will work on cutting-edge 100,000-pound autonomous robots and engineer complex systems at the intersection of hardware, software, robotics, and AI.

## About the Role

Own the transition from manually tuned MPC-based vehicle control to learning-driven control policies that adapt across vehicles with minimal human intervention, while maintaining safety and interpretability.

Core Responsibilities

- Practical understanding of vehicle dynamics and system identification
- Practical experience in generating test plans, collecting real-world data, and using real-world data for system identification of plant models for automatic control.
- Design and implement learning-based control approaches (imitation learning, reinforcement learning, hybrid MPC + learning)
- Reduce dependence on hand-tuned control parameters through data-driven methods
- Integrate learned controllers into the existing vehicle control stack safely and incrementally
- Define interfaces between classical control (MPC, PID, state estimation) and learning-based components
- Work closely with the Principal Controls Engineer to translate classical control insights into learning-friendly formulations
- Establish validation criteria for learned control policies before real-vehicle deployment

Required Qualifications

- 2-3 years of experience with experimental data collection and data analysis to estimate parameters of a plant model used for automatic control
- Strong software engineering skills in C, C++, or Python (production-quality code)
- Deep understanding of modern robotics control systems
- Experience with learning-based control or policy optimization for real-world systems
- Comfort working close to hardware and real-time constraints

## Preferred Qualification

- Reinforcement learning or imitation learning for control
- Model-based RL, residual learning, or hybrid MPC architectures
- Control under uncertainty and partial observability
- Debugging and validating control systems on physical platforms

Bonus Points

- Experience deploying learned controllers on vehicles or mobile robots
- Familiarity with safety-constrained learning methods
- Background spanning both classical and modern control theory

Teleo is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. All qualified people are encouraged to apply.

## About Teleo

## Company Overview
- **One-liner**: Teleo converts existing fleets of heavy equipment into semi-autonomous robots that operators can control remotely, improving safety and productivity in construction and mining.
- **Entity Type**: Private, acquired by HavocAI in March 2026 (now an operating subsidiary)
- **Headquarters**: Palo Alto, California, United States
- **Founded**: 2019
- **Founders**: Vinay Shet (CEO) and Rom Clement (CTO)

## Core Business
- **Primary Industry**: Automation Machinery Manufacturing, Robotics, Construction Technology
- **Target Customers**: B2B, serving construction companies, mining operators, and heavy equipment fleet owners
- **Mission/Purpose**: To revolutionize heavy equipment operations by bringing supervised autonomy to existing machines, making worksites safer and more productive while addressing labor shortages

## Products & Services
- **Supervised Autonomy Retrofit Kit**: A hardware/software system that retrofits existing heavy equipment (dozers, excavators, etc.) with teleoperation and semi-autonomous capabilities. Operators control machines from a remote desk, switching between machines and job sites instantly.
- **Remote Operations Platform**: A software platform enabling operators to manage multiple machines from a safe, comfortable remote workstation.
- **Analytics**: Provides operational performance analytics to improve fleet efficiency.

## Market Standing
- **Valuation**: Not publicly disclosed (acquired by HavocAI in 2026)
- **Total Funding**: $28.2M – $29.8M (conflicting reports) across 4 rounds, including a $150K accelerator round and multiple Series A rounds led by UP.Partners
- **Key Metric**: Annual revenue of approximately $1.8M (pre-acquisition estimate); employee count of 43–56 (varying sources)
- **Notable Investors**: UP.Partners (lead), Trucks Venture Capital, F-Prime Capital
- **Growth Signals**: 
  - Acquired by HavocAI in March 2026, signaling strategic value in defense/autonomy space
  - Named to BuiltWorlds 2026 Robotics Top 50 in Automated Machinery & Related Solutions – Earthmoving & Excavation
  - Active job postings (3 open roles as of recent data)
  - LinkedIn followers: 4,441 (growing ~1%/month, ~19%/year)

## Competitive Advantages
- **Retrofit Approach**: Works with existing heavy equipment fleets rather than requiring new machines, lowering adoption barriers for customers.
- **Supervised Autonomy**: Combines remote operations with autonomous capabilities — machines handle mundane tasks autonomously, operators step in for complex tasks — allowing one operator to manage multiple machines.
- **Patented Safety & Control Systems**: Multiple active patents covering teleoperator workflow assignment and control station safety.
- **HavocAI Backing**: Now part of a larger autonomy company with resources across sea, air, and land domains, expanding market reach.

## Strategic Focus
- Integration under HavocAI to extend all-domain collaborative autonomy capabilities
- Serving construction and mining customers with safe, practical autonomy solutions
- Expanding remote operator capabilities to address industry labor shortages
- Continued product development in supervised autonomy for heavy equipment

## Why Work Here
- **Engineering Focus**: 11 of 17 employees (pre-acquisition) in technical roles — strong engineering culture with technologies including Python, PyTorch, C++, TypeScript, React, AWS, ROS, and Linux
- **Location**: On-site in Palo Alto, CA (292 Lambert Ave — the HQ)
- **Culture**: Startup environment focused on solving real-world problems in construction and mining; emphasis on safety and productivity innovation
- **Recent Hires From**: Notable companies including Nuro, Dusty Robotics, Lyft, Archer, Tesla — suggests high-caliber engineering talent
- **Growth Trajectory**: Acquired by HavocAI with resources for scale; opportunity to work on cutting-edge robotics and autonomy tech
- **Current Openings** (as of recent): Senior Mechanical Engineer (Vehicle Integration & Validation), Lead Perception Engineer, Logistics & Inventory Associate

## Sources
1. [LinkedIn Company Page](https://linkedin.com/company/teleo-ai)
2. [CB Insights Profile](https://www.cbinsights.com/company/teleoai)
3. [PitchBook Company Profile](https://pitchbook.com/profiles/company/433416-25)
4. [Tracxn Company Profile](https://tracxn.com/d/companies/teleo-ai/__UCxVxpZgXtnE0Bud-VUXpyEciI445vcn7CaUSYy5OhA)
5. [Lever Careers Page](https://jobs.lever.co/teleo)
6. [Company Website](https://teleo.ai)
7. [LinkedIn Post (BuiltWorlds Award)](https://linkedin.com/company/teleo-ai)

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