{"id":68557,"url":"https://alion.io/job/aquabyte-embedded-software-engineer","title":"Embedded Software Engineer","company":{"id":26848,"name":"Aquabyte","domain":"aquabyte.ai","url":"https://alion.io/company/aquabyte","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":null},"role":"Hardware","role_family":"Hardware","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":130000,"max":190000,"currency":"USD","period":"year","gross":null,"usd_annual":190000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"C++","optional":false},{"name":"Computer Vision","optional":false},{"name":"Go","optional":false},{"name":"Linux","optional":false},{"name":"LoRaWAN","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"RTOS","optional":false},{"name":"Rust","optional":false},{"name":"TCP/IP","optional":false},{"name":"Wi-Fi","optional":false}],"status":"live","first_seen_at":"2024-10-02T15:57:47Z","employer_posted_date":"2024-10-02","last_verified_at":"2026-10-17T15:10:17Z","board_verified":true,"closed_at":null,"days_open":745,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":744},"description":"Our mission\nAquabyte is on a mission to revolutionize the sustainability and efficiency of aquaculture. By making fish farming cheaper and more viable than livestock production, we aim to mitigate one of the biggest causes of climate change and help prepare our planet for impending population growth. Aquaculture is the single fastest growing food-production sector in the world, and now is the time to define how technology is used to harvest the sea and preserve it for generations to come.\nWe are a diverse, mission-driven team that is eager to work alongside kindred spirits. If this vision makes you smile, gives you goosebumps, or otherwise inspires you please get in touch.\nOur product\nWe are currently focused on helping salmon farmers better understand their fish populations and make environmentally-sound decisions. Through custom underwater cameras, computer vision, and machine learning we are able to quantify fish weights, detect the health status, and generate optimal feeding plans in real time. Our product operates at three levels: on-site hardware for image capture, cloud pipelines for data processing, and a user-facing web application. As a result, there are hundreds of moving pieces and no shortage of fascinating challenges across all levels of the stack.\nAbout The Edge Systems Team:\nEdge engineering is responsible for the hardware and software orchestrating the hardware installed at fish farms around the world. Our goals are to create autonomous, reliable, bandwidth-light, long-lasting, robust, remote-debuggable, fail-safe, and easily deployable underwater cameras and sensors.\nWe work with world-class mechanical engineering firms and optical consultants to spec the underwater equipment we deploy. The edge engineering team writes software and procedures to make quality testing of these cameras as easy as possible for the field team in Norway. The types of tests we orchestrate are hardware burn-in, optical quality testing in-air and in-water, sensor calibration and verification, and stereo camera calibration.\nThe edge team also writes software to make it easy for the field team to successfully deploy and configure our hardware at the farm. As it’s often rainy in Norway and the Internet may not yet be set up, our debugging tools need to operate wirelessly and allow a field technician to interface with the hardware from their phones.\nThe edge team is responsible for designing the network, cellular backup system, and mesh network of devices at a farm. We plan for failure, and build in redundancies where possible. Internet can go out for hours and there’s only so much data we can uplink. Boats may park between our antennas.\nAs Aquabyte evolves, more products will be built on-top of the pixel and sensor data we collect. In order to scale, these algorithms need to live on the edge. We work closely with the machine learning team to help move their algorithms safely from the cloud to the edge.\nWe are responsible for our own Linux build process and the process of safely deploying software to the devices in the field.\nThis role is flexible and is based out of our Bay Area office and involves occasional travel to Norway and Chile.\nJob Responsibilities\nInterface with sensors; cameras; mesh, wireless, and cellular networks to create robust, reliable, and remote data collection and processing systems\nDevelop on ARM-based embedded platforms using C, C++, python, golang or rust\nImprove our embedded Linux build and deployment process\nDevelop software to automate hardware testing procedures\nBuild diagnostic and configuration tooling to enable our field team to interface with our hardware wirelessly from their phones.\nEnable our research team to try new machine learning models on real hardware\nParticipate in hardware specifications for our next generation equipment\nParticipate in on-call for diagnosing and fixing device issues remotely and implementing procedures and tooling to help enable the field team to self-diagnose and fix issues themselves\nQualifications\nEngineering or CS degree.\nSoftware development on an embedded device\nExperience writing and building software.\nProfessional experience with C, C++, Golang, Python or Rust.\nDesired but Not Required\nSolid understanding of TCP/IP\nReal-Time Operating Systems (RTOS)\nBuildroot, Yocto Project, toolchains, uBoot, UART, SPI, I2C interfaces\nExperience with WiFi, BLE, LoRaWAN, Mesh Networking, Cellular Networks\nSelecting hardware targeted for harsh environmental conditions\nAbility to read a schematic\nExperience with cloud environments such as AWS.\nExperience deploying to off-site hardware.\nProfessional experience working with cameras.\nBuild and maintain fleet operations tools for monitoring, notifications, trending, and analysis.\nExperience at a small & quickly growing startup\nBenefits\nCompetitive salary and equity\nUnlimited vacation policy\nFlexible working hours + hybrid work policy\nMedical, vision, & dental insurance\nRetirement matching plan\nPotential travel to Norway\nEvolve in a fast-paced environment\nBe able to shape a business in its early days\nGet ideas, feedback, and suggestions from other best-in-their-field colleagues\nMentorship opportunities, we'll be dedicated to investing in you and supporting you as you grow","description_format":"text","description_chars":5252,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Dental insurance","Equity","Flexible schedule","Hybrid work","Retirement plans"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Aquaculture","AgTech","Computer 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