Full-Time

Senior Software Engineer

Backend

Posted on 9/27/2025

Chef Robotics

Chef Robotics

51-200 employees

Delivers flexible robotics for food production

Compensation Overview

$150k - $240k/yr

San Francisco, CA, USA

In Person

Category
Software Engineering (1)
Required Skills
Kubernetes
Microsoft Azure
FastAPI
Python
JavaScript
MySQL
Machine Learning
Postgres
GraphQL
Docker
TypeScript
AWS
Next.js
REST APIs
Flask
Django
Google Cloud Platform
Requirements
  • Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
  • 7+ years of professional experience in backend development roles with demonstrated leadership experience
  • Expert knowledge of relational databases (MySQL, PostgreSQL) including schema design, optimization, and administration
  • Strong proficiency with Python and JavaScript/TypeScript with advanced software engineering skills
  • Extensive experience leading projects with at least two web frameworks: Flask, FastAPI, Django, Node.js, or Next.js
  • Proven experience designing and implementing RESTful and GraphQL APIs at scale
  • Advanced understanding of containerization (Docker) and orchestration (Kubernetes) technologies
  • Experience with cloud infrastructure and deployment (AWS, GCP, or Azure) in production environments
  • Proven experience leading complex backend projects and mentoring junior engineers
  • Understanding of data requirements for robotics or automation systems
  • Experience with real-time or near-real-time systems and high-performance backend architecture
  • Background in developing secure, reliable systems with high availability requirements
  • Knowledge of continuous integration and continuous deployment practices and infrastructure-as-code principles
  • Familiarity with AI/ML deployment workflows and requirements
  • Strong leadership and mentoring skills with ability to drive technical initiatives
  • Excellence in technical communication with ability to explain complex systems to diverse audiences
  • Proactive mindset in identifying potential issues and implementing scalable solutions
  • Comfort with working in a fast-paced startup environment with startup-oriented hours
  • Commitment to working onsite five days a week to contribute to positive in-office culture
  • Passion for robotics and automation technology
  • Collaborative approach to cross-functional engineering teams
Responsibilities
  • Lead the design, implementation, and optimization of database schemas to support robot operations, telemetry, recipe management, and system analytics
  • Develop robust data migration strategies and version control for database schema evolution
  • Implement efficient query optimization and indexing strategies to support high-throughput robot operations
  • Establish data integrity protocols and backup systems to ensure operational continuity across customer deployments
  • Create scalable data access layers that balance security, performance, and maintainability
  • Mentor team members on database design patterns and optimization techniques
  • Lead the development and maintenance of scalable APIs to serve robot control systems, dashboards, and monitoring tools
  • Design and implement secure authentication and authorization mechanisms across backend services
  • Develop robust middleware for processing and validating data between robotics subsystems
  • Create service interfaces that enable efficient communication between robotics components and cloud services
  • Collaborate with frontend and robotics engineers to ensure cohesive integration of backend services
  • Establish API design standards and best practices for the engineering team
  • Lead implementation of backend services that support machine learning pipelines for robot vision and motion planning
  • Develop sophisticated APIs for model deployment, monitoring, and version management across robotics fleets
  • Create efficient data storage and retrieval systems for training datasets and inference results
  • Design and implement systems to collect and process performance metrics from AI components
  • Collaborate with ML engineers to optimize data flow for training and inference processes
  • Drive architecture decisions for AI/ML infrastructure and scalability
  • Lead implementation of comprehensive logging, monitoring, and alerting for backend systems
  • Develop diagnostic tools and dashboards for operational visibility across distributed robotics deployments
  • Establish performance benchmarks and optimize systems to meet latency requirements for real-time operations
  • Implement fault-tolerant design patterns to ensure reliability in production environments
  • Create and maintain technical documentation for backend systems and mentor team on best practices
  • Drive technical initiatives for system scalability and performance optimization
  • Designing and implementing scalable database architecture for multi-site robotics deployments
  • Leading development of real-time APIs for robotics control and monitoring systems
  • Architecting AI/ML infrastructure for model deployment and performance monitoring
  • Establishing backend system reliability and performance monitoring frameworks
  • Mentoring engineering team on backend best practices and system design principles
Desired Qualifications
  • Experience with time-series databases (InfluxDB, TimescaleDB) for telemetry data
  • Knowledge of message queue systems (Kafka, RabbitMQ) for distributed systems
  • Familiarity with WebSockets for real-time communication
  • Experience with Redis for caching and pub/sub patterns
  • Background in manufacturing, food production, or industrial automation
  • Experience developing systems that interface with robotics hardware
  • Knowledge of ROS (Robot Operating System) or similar frameworks
  • Startup experience with track record of shipping working products under tight deadlines
  • Experience with microservices architecture and distributed systems design

Chef Robotics provides flexible, machine learning-enabled robotic systems for food production to help food companies cope with labor shortages and high staff turnover. The robots can perform multiple tasks across different production lines and environments, with ongoing maintenance and support. Unlike rigid automation, their ML-driven adaptability lets one set of robots handle diverse tasks, reducing waste and increasing throughput. The goal is to help food companies scale production and cut costs from day one, contributing to a more resilient US food supply.

Company Size

51-200

Company Stage

Series A

Total Funding

$77M

Headquarters

San Francisco, California

Founded

2019

Simplify Jobs

Simplify's Take

What believers are saying

  • Produced over 104 million servings for Amy's Kitchen and Sunbasket, displacing 10% staff since 2022.
  • Raised $43.1M in March 2025 to expand RaaS model into UK and Germany markets.
  • New capabilities automate meat, produce, and baked goods packing across US, Canada, UK.

What critics are saying

  • ABB and Fanuc displace Chef with superior vision robots in high-volume CPG meat packing within 6-12 months.
  • Miso Robotics' Flippy erodes Chef's ghost kitchen expansion via cooking deployments since 2021.
  • $26.75M Silicon Valley Bank debt triggers dilution if RaaS defaults rise in 12-18 months.

What makes Chef Robotics unique

  • Chef Robotics' AI robots automate deformable food packing like sauce sachets using real-time computer vision.
  • Chef+ doubles ingredient capacity while matching worker footprint for tight production spaces.
  • Robot-to-robot communication achieves 150 trays per minute on shared conveyors without infrastructure changes.

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Benefits

Flexible Work Hours

Remote Work Options

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

5%

2 year growth

0%
PR Newswire
Apr 9th, 2026
Chef Robotics' AI models now automate meatpacking tray assembly

Chef Robotics has announced its physical AI models can now automate tray assembly for meatpacking, handling raw, frozen and precooked proteins including pork loin fillets, chicken breasts, steaks and sausages. The application addresses a historically difficult automation challenge caused by meat's irregular, deformable and variable characteristics. Built on Chef's piece-picking capability, the system uses AI and computer vision trained on extensive data covering protein appearance, physical properties and handling characteristics. Key features include detecting and reorienting pieces mid-motion regardless of original position, completing assembly in a single automated pass, and ensuring consistent spacing through vision-based calculations. The meatpacking capability is available in the US, Canada and the UK through Chef's robotics-as-a-service pricing model. Chef Robotics has produced over 101 million servings in production.

PR Newswire
Mar 12th, 2026
Chef Robotics launches robot-to-robot communication for high-speed food production lines

Chef Robotics has announced robot-to-robot communication technology, enabling multiple robots on shared conveyor lines to coordinate and increase throughput in food manufacturing facilities. The system allows Chef robots to communicate directly via built-in wireless radios, sharing real-time data about tray positions and orientations. When one robot deposits an ingredient, it immediately alerts downstream robots, which then know precisely which tray to target. Each robot maintains its own perception system whilst wireless communication keeps them synchronised. The technology requires no additional infrastructure and works across various ingredients without ingredient-specific models. In some configurations, Chef robots can reach speeds of up to 150 trays per minute. The company, which has produced over 96 million servings, offers the capability through its robotics-as-a-service model in the US, Canada and UK.

PR Newswire
Mar 3rd, 2026
Chef Robotics unveils conveyor connect for AI-enabled meal assembly robots

Chef Robotics has launched Conveyor Connect, enabling its AI-powered meal assembly robots to communicate with various conveyor types, including continuous belt, chain and indexing conveyors. The system is already deployed in production across multiple customer facilities. The technology uses a wireless, waterproof companion box that attaches to existing conveyor control systems, allowing Chef robots to read belt speeds in real time, control conveyor movement and coordinate stop-and-go operations. This eliminates the need for infrastructure changes and enables robots to move freely between stations. San Francisco-based Chef Robotics has produced over 94 million servings in production. The Conveyor Connect capability is available to food manufacturers in the US, Canada and UK through Chef's robotics-as-a-service pricing model.

The Robot Report
Dec 20th, 2025
Chef Robotics launches its most advanced assembly robot yet

Chef Robotics launches its most advanced assembly robot yet. Chef Robotics Inc. yesterday introduced Chef+, which it said is its most advanced meal-assembly robot yet. The San Francisco-based company said it is an innovator in artificial intelligence-enabled meal assembly for the food manufacturing industry. Built on insights from more than 80 million servings in production, Chef+ delivers reliability, double the ingredient capacity, a reduced footprint, improved food safety, and enhanced usability and performance compared with previous models, said Chef Robotics. The company raised $43 million earlier this year in Series A funding. It has used that investment to expand its business and innovating with new capabilities, such as those in Chef+. Chef+ address operational constraints. Food manufacturers face critical operational constraints: Limited production floor space restricts equipment placement, frequent ingredient refills disrupt production throughput, and stringent food safety standards demand easy-to-clean equipment. Chef+ is explicitly engineered to address these challenges through advancements in six key areas: * Doubled ingredient capacity: Ingredient pans are twice the volume of previous models, significantly extending the time between refills. This allows refill runners to load ingredients less frequently, reducing labor touchpoints and increasing productivity. The increased capacity is particularly beneficial for low-density and voluminous ingredients, such as leafy greens, and for large portion deposits, such as pasta. * Reduced footprint: Despite its doubled capacity, Chef+ maintains the same footprint as a worker. This thinner design allows facilities to deploy robots in tight spaces and place two production lines back to back, optimizing valuable floor space, according to Chef Robotics. * Enhanced reliability: Drawing on extensive runtime at customer facilities, Chef+ features integrated electrical enclosures that conceal all wiring in sealed tubes, increasing mean time between failures (MTBF). The robot features IP cameras, which are more reliable than USB-C cameras for cold production environments. Chef+ also includes an integrated water separator that captures excess moisture in pneumatic tubes, ensuring that air remains completely dry. It uses an array of dome antennas for improved Wi-Fi connectivity. * Advanced food safety: The Chef+ frame replaces the two front closed tubes with an open-angle iron frame. This makes surfaces easier to clean and eliminates hidden crevices where residue can accumulate, helping manufacturers meet strict food safety and sanitation standards. * Improved usability: Chef+ features several functions to enhance usability and reduce setup and changeover time. Ingredient pans slide easily into the robot, thanks to an integrated locking mechanism. P-CAP technology makes the touchscreen easier to use with gloves in cold production environments. In addition, a daisy-chain power configuration allows manufacturers to connect multiple robots to a single ceiling power source. Finally, Chef+ includes self-leveling feet and an integrated handle, making it easier to move around on the production floor. * Enhanced performance: Chef+ delivers higher CPU and GPU processing power and adapts to variable ingredient types in real time, claimed Chef Robotics. It also includes a three-camera vision system to accurately track conveyor speed and trays for precise ingredient placement. Chef+ has undergone rigorous testing in the company's cold-room lab environment and is already running in production at several customer sites. The robot is now widely available to food manufacturers across the U.S., Canada, and the U.K. New 'pat down' gripper attachment flattens food. Chef Robotics said its new "pat-down" capability takes on the manual task of flattening ingredients to ensure uniform tray coverage and improved sealing. By automating this repetitive, labor-intensive process, manufacturers can enhance meal presentation and reduce costs while addressing critical labor shortages. The new capability fully automates meal-flattening tasks using vibration technology in the end effector along with a flat, cross-slotted utensil. This new utensil is interchangeable with Chef's depositing utensils and features a cleanable, rounded-edge design that meets food safety standards and cleaning protocols. The solution employs AI-powered computer vision software to detect and track trays on the conveyor in real-time, understanding their position and orientation. This capability enables the robots to handle variations in tray positions, line stoppages, and speed changes that traditional automation cannot manage, asserted Chef Robotics. For high-volume operations, the pat-down capability integrates with Chef's robot-to-robot (R2R) system, enabling multiple robots to coordinate and distribute tasks by alternating trays for increased throughput. Production lines can also use robots for both meal assembly and pat-down operations simultaneously, with one robot depositing ingredients while another flattens meals. The pat-down capability eliminates a strenuous, repetitive task, freeing up workers for higher-value tasks while reducing overall production costs and preventing repetitive stress injuries. Beyond labor cost reduction, the solution addresses downstream operational challenges such as spillage during sealing, machine downtime, rejected trays, and food waste. Some Chef customers have already deployed the pat-down capability on their production lines, ensuring consistent presentation and tray sealing for frozen meals such as mac and cheese. The capability is now widely available to food manufacturers in the U.S., Canada, and the UK. As part of Chef's robotics-as-a-service (RaaS) pricing model, the capability requires no upfront capital investment.

TechOrange
Jul 7th, 2025
Chef Robotics secures $20.6M funding success

Chef Robotics, a Silicon Valley startup, has developed AI robots for food production and packaging, addressing labor shortages in the food service industry. Despite initial setbacks due to a "grasping problem" in fast food, the company pivoted to the frozen food and central kitchen markets. They recently secured $20 million in Series A funding. Their AI system, ChefOS, enhances robot flexibility, enabling them to handle diverse ingredients, with plans to expand into commercial kitchens.

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