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Build Stat Sniper with us

We're a small engineering team building the free AI sports betting app — Chad AI picks and predictions, a prop tracker that grades itself, and a social network for bettors. Five engineering roles are open.

Stat Sniper Inc. was founded in 2024 on the belief that bettors deserve honest tools. Chad AI publishes a confidence rating on every pick and is graded in the open, win or lose. The prop tracker settles every logged bet against the final box score. The whole product is free. None of that works unless the engineering underneath it is correct, fast, and observable while games are live.

That is the work. Sports data is messy, arrives from a dozen providers in a dozen shapes, and is only useful for the few hours it stays current. We're looking for engineers who find that interesting rather than annoying — people who want to own a surface end to end and see it in front of users the same week.

Open roles

Every role is full time and based in Newport Beach, CA. Open a role to see what you'd own and what we're looking for.

Go EngineerBackend · Newport Beach, CA · Full time+

Own the services that move sports data. Odds, scores, injuries, and lineups arrive from a dozen upstream feeds at different shapes and cadences, and everything downstream — Chad AI's picks, the prop tracker's grading, live game chat — is only as good as that pipeline. You'll build the Go services that ingest, normalize, and fan that data out, and keep them correct while games are live.

What you'll do

  • Build and operate high-throughput ingestion services for odds, box scores, injuries, and lineups.
  • Design the normalization layer that turns a dozen upstream provider schemas into one internal model.
  • Keep latency low and correctness absolute during live games, when a stale score is worse than no score.
  • Instrument the pipeline so a broken upstream feed surfaces as an alert, not as a user-visible wrong number.

What we're looking for

  • Production Go experience with concurrent systems — goroutines, channels, context, and backpressure.
  • Comfort with Postgres schema design and query performance at scale.
  • Experience with event-driven architecture (Pub/Sub, queues) and idempotent consumers.
  • A bias toward observability: you ship metrics and traces alongside the feature.
Apply for this role
Full Stack TypeScript EngineerWeb · Newport Beach, CA · Full time+

Build the web surface end to end — the marketing site, the content platform, and the web app. Our front end is Next.js App Router on React 19 with Tailwind, backed by a Node server on Cloud Run and content in a headless CMS. You'll work across that whole stack, from a GROQ query to a server component to the layout it renders.

What you'll do

  • Ship features across the stack: Next.js App Router routes, server components, API handlers, and data access.
  • Hold the line on Core Web Vitals — this site lives or dies on organic search, so LCP and CLS are features.
  • Build against a headless CMS so non-engineers can edit copy without a deploy.
  • Extend the design system rather than working around it, keeping one set of component patterns site-wide.

What we're looking for

  • Strong TypeScript, including generics and the discipline to type data at the boundary.
  • Deep React experience and a real understanding of the server/client component split.
  • Working knowledge of SEO fundamentals: structured data, canonicals, hreflang, and why they matter.
  • Comfort with SQL and with fetching from a headless CMS.
Apply for this role
Data ScientistModeling · Newport Beach, CA · Full time+

Chad AI publishes a win probability for every pick it makes and grades itself in the open, win or lose. That only works if the numbers are honest. You'll own the models behind those probabilities — player prop projections, game outcomes, and the calibration work that keeps a stated 60% actually hit about 60% of the time.

What you'll do

  • Build and maintain projection models for player props, spreads, totals, and moneylines.
  • Own calibration and backtesting, and publish the accuracy numbers the product shows users.
  • Find edge by comparing model output against market lines, and quantify it honestly.
  • Turn messy historical sports data into features that survive contact with a live slate.

What we're looking for

  • Strong applied statistics: probability calibration, Bayesian methods, and time-series validation.
  • Fluent Python with the modeling stack (pandas, scikit-learn, and a gradient-boosting library).
  • Experience evaluating models against a moving benchmark rather than a static holdout set.
  • The instinct to distrust a result that looks too good — and the rigor to find out why it does.
Apply for this role
Senior Python EngineerData Platform · Newport Beach, CA · Full time+

Take the models from research to production and keep them there. You'll build the pipelines that assemble training data, the services that serve predictions during a live slate, and the grading jobs that score every pick against the final box score — then make all of it reliable enough that nobody has to babysit it on a Sunday.

What you'll do

  • Build production data pipelines that turn raw feeds into model-ready features on a schedule.
  • Ship model-serving services on Cloud Run with predictable latency under slate-day load.
  • Own the grading jobs that settle every logged bet against the official result.
  • Set the engineering standard for the data codebase: typing, tests, and reproducible runs.

What we're looking for

  • Senior-level Python with real production ownership, not notebook-only experience.
  • Experience with orchestration (Airflow, Prefect, or similar) and with idempotent, retryable jobs.
  • Strong SQL and comfort designing analytical schemas in Postgres.
  • A track record of taking someone else's model and making it run every day without drama.
Apply for this role
Senior DevOps EngineerInfrastructure · Newport Beach, CA · Full time+

Own the platform everything else runs on. We're on Google Cloud — Cloud Run, Kubernetes, Cloud SQL, Pub/Sub, Cloud Build — serving a mobile app, a web app, and a content site that cannot afford to be slow or down during a live slate. You'll make deploys boring, make failures visible, and keep the bill proportionate to the traffic.

What you'll do

  • Own CI/CD end to end so a merge reaches production safely without a human in the loop.
  • Run and tune GKE and Cloud Run workloads for traffic that spikes hard around game times.
  • Build the observability layer — metrics, logs, traces, alerts that fire on user impact, not on noise.
  • Manage infrastructure as code, and treat cloud spend as an engineering metric.

What we're looking for

  • Senior experience operating production workloads on GCP (or equivalent depth on AWS).
  • Real Kubernetes operations experience, not just authoring manifests.
  • Infrastructure as code (Terraform or similar) and container build pipelines you've owned.
  • Security fundamentals: secret management, least-privilege IAM, and a credential that never reaches a client bundle.
Apply for this role

Why work here

Small team, real ownershipYou will own a surface outright, not a ticket queue. The work you ship is in front of users within days, and you can point at the part of the product that is yours.
Ship to production quicklyShort review cycles and a deploy pipeline built so that merging is the hard part, not releasing. No quarterly release trains.
Modern stack, no legacy taxGo, TypeScript, Python, Flutter, and Postgres on Google Cloud. The codebase is young enough that the right fix is usually the one you get to make.
Sports, with actual dataLive odds, box scores, and a model that grades itself in public. If you like problems where the answer shows up on a scoreboard a few hours later, this is that.

How hiring works

1. ApplyEmail hello@statsniper.com with the role in the subject line, your resume or GitHub, and a short note on what you'd want to own.
2. Intro callA 30-minute conversation about your background, what you're looking for, and what the role actually involves day to day.
3. Technical conversationA working session on a real problem from our domain. No algorithm trivia and no unpaid take-home project.
4. OfferA final conversation with the founding team, then a decision. We aim to go from first email to offer in under two weeks.

Don't see your role?

We hire for fit before headcount. If you're strong and the product interests you, send a note anyway and tell us what you'd want to build.

Email hello@statsniper.com

More about the company on our about page.

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