Careers

Build Stat Sniper with us

We're a small, remote-first 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, anywhere in the world.

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, fully remote, and open to candidates anywhere in the world. Open a role to see what you'd own and what we're looking for.

Go EngineerBackend · Remote (worldwide) · 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 in Go, running as containers on ECS Fargate and Cloud Run.
Design the normalization layer that turns a dozen upstream provider schemas into one internal model in Postgres.
Use DynamoDB for the hot read paths that back live scores and odds, and Postgres for everything relational behind them.
Archive every raw upstream payload to S3 so a bad transform can be replayed instead of re-fetched.
Keep latency low and correctness absolute during live games, when a stale score is worse than no score.

What we're looking for

Production Go experience with concurrent systems — goroutines, channels, context, and backpressure.
Strong Postgres fundamentals: schema design, indexing, and query performance at scale.
DynamoDB experience beyond CRUD — access-pattern-first table design, partition keys, and secondary indexes.
Comfort shipping containers to AWS (Fargate, ECR, S3) and GCP (Cloud Run, Pub/Sub) without treating either as magic.
A bias toward observability: you ship metrics and traces alongside the feature.

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Full Stack TypeScript EngineerWeb · Remote (worldwide) · 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, served from containers on Cloud Run, with Firebase behind the authenticated surfaces and Postgres behind the data-heavy ones. You'll work across that whole stack, from a 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.
Work against Firebase (Auth and Firestore) for user-facing state, and read-only Postgres for sports and stats data.
Serve images and static assets out of S3 and Cloud Storage with cache headers that hold up under a traffic spike.
Hold the line on Core Web Vitals — this site lives or dies on organic search, so LCP and CLS are features.
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.
Hands-on Firebase (Auth, Firestore, security rules) and comfortable writing SQL against Postgres.
Experience deploying containerized apps to Cloud Run, Fargate, or equivalent — you can debug your own deploy.
Working knowledge of SEO fundamentals: structured data, canonicals, hreflang, and why they matter.

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Data ScientistModeling · Remote (worldwide) · 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.
Work from a historical store of box scores and odds snapshots in Postgres and S3, and ship the features your models need.
Find edge by comparing model output against market lines, and quantify it honestly.

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).
Confident SQL against Postgres, and comfort reading large Parquet datasets straight out of S3.
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.

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Senior Python EngineerData Platform · Remote (worldwide) · 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 land raw feeds in S3 and modeled tables in Postgres on a schedule.
Ship model-serving containers to Cloud Run and ECS Fargate with predictable latency under slate-day load.
Serve precomputed features and predictions from DynamoDB where the app needs single-digit-millisecond reads.
Own the grading jobs that settle every logged bet against the official result, and the Firebase writes that surface it in the app.
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.
Practical AWS and GCP experience — S3, DynamoDB, and Fargate on one side, Cloud Run and Firebase on the other.
A track record of taking someone else's model and making it run every day without drama.

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Senior DevOps EngineerInfrastructure · Remote (worldwide) · Full time+

Own the platform everything else runs on. We are genuinely multi-cloud: Kubernetes, Cloud Run, Cloud SQL, Pub/Sub, and Firebase on GCP, alongside ECS Fargate, DynamoDB, and S3 on AWS — 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

Run and tune Kubernetes (GKE and EKS) plus serverless container workloads on Cloud Run and ECS Fargate.
Own the data layer's operations: Cloud SQL and Postgres tuning, backups and failover, DynamoDB capacity and cost.
Manage S3 and Cloud Storage lifecycle, encryption, and IAM so storage stays cheap and correctly locked down.
Own CI/CD end to end so a merge reaches production safely without a human in the loop.
Build the observability layer — metrics, logs, traces, alerts that fire on user impact, not on noise.
Manage infrastructure as code across both clouds, and treat cloud spend as an engineering metric.

What we're looking for

Senior experience operating production workloads on both AWS and GCP, or deep expertise in one and real fluency in the other.
Real Kubernetes operations experience — autoscaling, resource limits, rollouts, and debugging a wedged node — not just authoring manifests.
Hands-on with Fargate, S3, and DynamoDB on AWS, and Cloud Run, Cloud SQL, and Firebase on GCP.
Infrastructure as code (Terraform or similar) and container build pipelines you have owned.
Security fundamentals: secret management, least-privilege IAM, and a credential that never reaches a client bundle.

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Why work here

Remote, worldwideEvery role is fully remote and open anywhere in the world. We hire for the person, not the postcode, and there is no expectation that you relocate or sit in an office.

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.

Two clouds, modern stackGo, TypeScript, Python, and Flutter on AWS and GCP — Kubernetes, Fargate, Cloud Run, Postgres, DynamoDB, Firebase, and S3. The codebase is young enough that the right fix is usually the one you get to make.

Written by defaultA team spread across time zones only works if decisions live in writing rather than in a meeting you missed. Expect fewer calls and more context you can actually go back and read.

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 careers@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 careers@statsniper.com

More about the company on our about page.

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Build Stat Sniper with us

Open roles

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What we're looking for

What you'll do

What we're looking for

What you'll do

What we're looking for

What you'll do

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What you'll do

What we're looking for

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