About Mashgin
Mashgin powers the world's best checkout experience for over 40 million users. Customers just place their items on our kiosks and our AI rings up their entire order in less than a second. With Mashgin, lines are now optional.
Mashgin's technology powers over 1 billion transactions at your favorite locations, including over half of all US professional sports teams, 4,000 convenience stores, major airports, universities, and more.
We’re not just building cutting-edge AI—we’re creating real-world impact and unforgettable experiences. Backed by a well-funded Series B, we’re also one of the rare AI startups that’s already profitable.
Our secret? A culture of extreme ownership, autonomy, and customer obsession. At Mashgin, we are building something extraordinary by challenging conventional wisdom. We’ve thrown out the old rules to focus on what truly matters: creating a kickass product that makes people say, 'Wow'. We don’t care about short-term wins; we build systems that stand the test of time. If you thrive in a culture of excellence without compromise and want to see your work have an immediate, remarkable impact, you’re in the right place.
Position Summary
We're looking for an engineer to join a new team building features on top of in-store camera feeds (not the kiosk's own sensors, but the store's security/overhead cameras). Today that footage mostly just sits on-site, unused. This team will build the pipeline to get value out of it, whether that means analyzing it where it lives or pulling it into the cloud, across thousands of stores each with its own network constraints and camera hardware.
You'll be an early member of the team. That means writing the capture/ingestion code, dealing with real codec and streaming decisions (what to encode in, how to transport and play back efficiently over constrained store networks), figuring out what stays on-site versus what moves to the cloud, and getting the first features hooked up. This has a lot in common with building a video player/streaming stack. We need someone who's comfortable with some ambiguity: requirements that aren't fully defined yet, tooling you may need to build yourself, and a willingness to just build the thing rather than wait for a full spec. This is a hands-on coding role first, an infrastructure-design role second.
We maintain a flat, high-impact engineering culture where every engineer who joins our team carries the title of Member of Technical Staff.
What We Value:
- Impact: You will own significant responsibility and have total ownership over your work. We stay lean and efficient, so your work directly impacts the product we ship every day.
- Simplicity: Complexity is a waste of time here—we take pride in building things that just work.
- Hard Work: Forget the glamorous research papers. We prioritize the hard work it takes to achieve real-world clarity and accuracy. You will innovate relentlessly to push the boundaries of what’s possible in visual automation.
- Humility: No task is beneath you. Whether it's high-level architecture or grunt work to fix a bug, we check our egos at the door and get real work done.
- Ruthless Prioritization: If everything is on fire, nothing is. You will be expected to prioritize ruthlessly, cutting through distractions to focus on the most impactful product improvements.
- Customer Innovation: We are customer-centric, not customer-pleasing. You won’t bend to every client demand; you will let innovation drive the product forward to solve the real problems our users face.
- Efficiency: Meetings suck. We keep them short and only use them for alignment, giving you your time back to focus on real work.
You Will Be
- Writing the actual code, end to end, for a 0-to-1 pipeline: capturing feeds from in-store cameras, encoding, and getting that video where it needs to go, whether that's processed on-site or ingested and stored in the cloud, with no existing system to extend
- Making real codec and streaming-protocol decisions: encoding formats, bitrate/quality tradeoffs, adaptive streaming
- Making fast, pragmatic calls on architecture with incomplete information, and being fine revisiting them as real-world store conditions prove you wrong
- Getting the first feature or two working end-to-end (e.g. a monitoring view, or feeding footage into an early AI feature) to prove the pipeline works
- Working alongside a small, scrappy group across hardware, ML, and backend, figuring out together what "good" looks like, not inheriting a spec
- Dealing with the reality of store hardware: varying camera models, spotty or shared network connections, and physical sites you can't always control
- Doing whatever the moment calls for: debugging a flaky store network connection one day, writing a service to process or ship video the next
- Using AI coding tools to move fast: prototyping quickly, cutting through boilerplate, and iterating on architecture without getting bogged down
Minimum Qualifications
- 5+ years relevant coding experience, with a track record of shipping production code yourself.
- B.S. or higher in Computer Science (or equivalent work experience)
- Strong Python, plus comfort picking up whatever language or tool the problem actually needs
- Hands-on experience with video codecs, encoding, and streaming protocols: video player, media pipeline, or streaming platform work (think the engineering behind a video player at a company like Crunchyroll, Netflix, Twitch, YouTube)
- Experience touching both sides of a pipeline, edge/device code and cloud services, rather than only one layer
- Has built something from zero before: a new service, a new team's first system, a 0-to-1 project with no existing scaffolding
- Comfortable being one of the few people who know how a piece of the system works, at least for a while
Preferred Qualifications
- Startup experience, ideally on a small or newly-formed team where you wore multiple hats.
- Experience with camera or video hardware in the field (not just cloud-side video), especially dealing with inconsistent hardware or network conditions
- Comfortable working alongside ML engineers without needing to own the modeling work yourself
- Knowledge of infrastructure as code (Terraform, Ansible, etc.) and cloud environments like AWS
- Good knowledge of algorithms and data structures
- Fluent with AI coding tools (Claude Code, Cursor, etc.) as a default part of how you build and prototype
What We Offer
- An opportunity to work on a small, multidisciplinary team with the potential to break new ground in many different industries
- Excellent health, dental and vision insurance for you and your dependents
- 401k plan
- Flexible PTO policy
- Catered lunch in office with fully stocked snacks and beverages
- Pet insurance for your fur babies
- Voluntary life insurance plan
- Competitive salary and options in a small, rapidly scaling company
Mashgin is proud to be an equal opportunity employer. Individuals seeking employment at Mashgin are considered without regards to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.
Notice on fraudulent jobs
We have been made aware of instances of fraudulent job postings and/or fraudulent recruiting activity by bad actors, claiming to represent Mashgin. These fraudulent schemes often seek monetary contributions or payments from job seekers (such as for "start up costs" or "equipment"), or seek to collect sensitive personal or banking information from job seekers. These job postings and offers are not authorized by Mashgin, and Mashgin is not responsible for fraudulent offers or requests for personal information or payments. Mashgin will never ask for any financial commitment or contribution from a candidate at any stage of the recruitment process. Candidates who have questions about the validity of Mashgin job postings or offers should consult the job postings on our mashgin.com career site. If you think you've been scammed, please reference this site for more information. 
