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Platform Backend Engineer
- San Francisco, California, United States
- San Francisco, California, United States
À propos
We take pride in our self-starter culture where employees are enabled and encouraged to achieve their professional goals through leadership guidance, learning and development. Our philosophy is that careers are continuous journeys, and we dedicate time and offer resources so that employees can reach their full potential.
Benefits + Perks We value you at and outside of work and know your loved ones are important. Our benefits are designed to support you and your family’s health through life’s expected and unexpected events.
Our Benefits Include:
Competitive Salary + Stock Options
Health Care Coverage + Life Insurance + Health Savings Account + Flexible Spending
Account (includes spouse + children)
Flexible Vacation Policy
Adaptable Working Schedule and Environment
Our Perks Include:
Casual Dress Attire
Hybrid work flexibility
Catered Lunches, Snacks and Beverages
Commuter Savings Program
Company Outings
Designated Volunteering Hours + Group Volunteer Events
Sight Machine is proud to be an equal opportunity employer and considers candidates regardless of age, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Sight Machine also considers qualified applicants regardless of criminal histories, consistent with legal requirements.
About Sight Machine, Inc. Sight Machine strengthens manufacturers by providing the industry’s only standard data model and system-level visualization capabilities. By integrating all crucial data into a single innovative platform, everyone involved in the fabrication process can visualize, contextualize and examine data in one intuitive interface.
Sight Machine is committed and mission-driven to improve lives, strengthen communities and make the world cleaner through continuously re-envisioning manufacturing processes - making them more efficient, sustainable and absolute. Founded in Michigan in 2011 and expanded to San Francisco in 2012, Sight Machine blends the spirit of technology innovation and the down to earth style of Detroit manufacturing. Our team includes early leadership from Yahoo, Tesla Motors and Oracle. Together, we share wide industry knowledge and a commitment to advance manufacturing to a more sustainable future.
At Sight Machine, you will work with manufacturing leaders in the automotive, medical device, apparel, construction, and pharmaceutical industries. You will have access to, and work with massive amounts of factory floor data to help uncover insights on how customers make products and develop solutions to pressing business problems. The platform solves problems like Extract Transform Load (ETL), information retrieval, data aggregation and analytics, factory automation, distributed computing, and security.
We place great value on professional, technical, and personal growth in an inclusive, collaborative environment. The ideal candidate will have a passion for technology and a strong can-do attitude.
About the role You may not have the five years of ML infrastructure experience the frontier labs are asking for yet. We’re not asking for it either. We want to see what you’ve already built, and we’re offering the environment, the data, and the problems to build the rest.
Sight Machine runs AI systems on some of the most complex, high-dimensional, real-world data out there. Not synthetic benchmarks or chat logs. Live factory floors with millions of sensor events per minute, across dozens of interconnected machines, in facilities run by some of the world’s largest manufacturers. The algorithms that work here work because they have to, and that makes this a genuinely great place to build a technical foundation.
As a Platform Backend Engineer, you’ll work on the core systems that ingest, model, and serve that data, building and maintaining the infrastructure that powers real-time AI insights at industrial scale. You’ll write code that runs in production, ships fast, and matters. We’ll ask to see what you’ve already built before we ask anything else.
This is a role for someone early in their career who is already running ahead of it. If you’re building things on nights and weekends because you can’t help yourself, and you’ve been using AI tools as a core part of how you work rather than a novelty, we want to talk.
What You’ll Actually Work On In your first year, you can expect to work on problems like these:
Building and optimizing ETL pipelines that ingest streaming sensor data from factory equipment at high volume and low latency. A slow query or a dropped event can have real operational consequences.
Designing and maintaining backend services that power real-time dashboards and AI model outputs used by plant operators and manufacturing executives.
Contributing to the automation and alerting layer of our platform, using AI tools to help us catch issues before our clients do.
Working on data modeling problems at the intersection of operational technology (OT) and modern data infrastructure, translating messy, heterogeneous factory data into a clean, queryable model.
Collaborating with forward-deployed engineers embedded at client sites to understand real-world constraints and bring those insights back into the platform.
You’ll work across a codebase that includes legacy systems and greenfield development. Both matter. We want engineers who can navigate inherited architecture and still ship clean, thoughtful work alongside it. We don’t expect you to walk in knowing all of this. We expect you to be the kind of person who digs in until you do.
What We’re Looking For We’re not focused on years of experience. We’re focused on what you’ve shipped, how you work, and whether you’re the kind of person who raises the bar for everyone around them. You won’t tick every box here, and that’s fine. Here’s what we actually care about:
A portfolio you’re proud of. Side projects, open-source contributions, AI-powered tools you built because you wanted to see if you could. We’ll ask to see what you’ve made, and a strong portfolio can outweigh time on a resume.
Real fluency with AI development tools. Not just Copilot for autocomplete, but agentic workflows, LLM-assisted pipelines, or tools you’ve built yourself on top of AI APIs. Show us how you actually work.
2+ years of professional software engineering experience, or less if your work speaks for itself.
Python as your primary language, with solid working knowledge of at least one other high-level language.
Strong foundations in data structures and algorithms, with some exposure to distributed systems and an interest in going deeper.
Experience with relational and NoSQL databases (MongoDB and PostgreSQL preferred).
Comfort with Unix/Linux environments.
You’ve shipped code in a system you didn’t build. You understand that a mature codebase is a record of decisions made under different constraints, not an invitation to start over, and you know how to move things forward without breaking what works.
Clear, direct communication. You don’t over-explain, but people know what you mean.
Nice to Have
Experience with Azure Cloud.
Exposure to ETL or large-scale data ingestion.
Familiarity with statistical technologies such as R.
Any exposure to Industrial IoT, manufacturing systems, or OT environments.
An active GitHub profile that tells a story about what you care about building.
Growth & Mentorship We’re building a team that takes craft seriously. You’ll work alongside engineers who push back in code reviews, pair on hard problems, and genuinely invest in making you better. We don’t expect you to arrive fully formed. We expect you to arrive hungry.
Engineers who ship, learn fast, and bring energy move quickly here. If you have a sense of where you want to be in two years, we want to help you get there.
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Compétences linguistiques
- English
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