Machine Learning Engineer (Remote - Americas)

San Francisco Bay Area /
Engineering – Machine Learning /
About Anomalo

Much like software before it, data is the next competitive battleground for modern enterprises. As a result, more and more companies are rushing to stand up their data stack and become data-powered organizations.

But every data-powered company quickly encounters one unfortunate fact: much of their data is missing, stale, corrupt, or prone to unexpected and unwelcome changes. As a result, companies spend more time dealing with issues in their data rather than unlocking that data's value. 

Anomalo addresses this problem by adding a new layer to the Modern Data Stack: a Data Quality Platform that monitors enterprise data to automatically detect and root-cause any data issues, thus allowing teams to resolve any hiccups with their data before making decisions, running operations, or powering models.

We help companies trust the data they use to make decisions and build products.

We work with some of the biggest brands like BuzzFeed, Discover Financial Services, and Substack. We're raised over $39m in seed and Series A funding backed by top-tier venture firms like Norwest Venture Partners, Foundation Capital, Two Sigma Ventures, and First Round Capital. We are building the platform that data-driven companies need to stay data-driven, and would love to have you join us for the ride!

What you’ll do as an ML Engineer at Anomalo

    • Own end-to-end development of machine learning product features (algorithm development, benchmarking, backend development, deployment, measurement, and ongoing operations) alongside product and engineering
    • Build machine learning algorithms that can run automatically on any structured data stored across hundreds of customer cloud data warehouse environments
    • Design algorithms that intelligently sample from very large tables to detect statistically significant anomalies
    • Build automated feature engineering, model training, and scoring pipelines that run in environments not directly under our control
    • Enhance our chaos library and benchmarking platform for measuring the effectiveness of our time series and unsupervised machine learning algorithms
    • Use explainability algorithms and visualizations to ensure we understand how our algorithms are working in production environments
    • Build custom visualizations that translate findings from our machine learning algorithms into actionable explanations for issues our customers can easily interpret
    • Develop new methods and approaches to monitoring or validating data at scale without creating false positive notifications
    • Expand our library of data checks for constrained anomaly detection and validation use cases

Qualifications you'll ideally have

    • 5+ years of machine learning engineering experience
    • Proficiency in Python is highly preferred
    • A strong first-principles approach to thinking about complex data and machine learning problems
    • Desire and ability to work at multiple levels of the machine learning stack (research, development, production)
    • Bachelor’s degree or higher in Mathematics, Statistics, Computer Science or a related discipline or equivalent practical experience

Nice to have

    • Experience with time-series algorithms
    • Experience with anomaly detection and data analytics
    • Experience deploying machine learning algorithms in SaaS platforms
    • Prior full-stack engineering experience

Technologies we use

    • Python (django / celery / numpy / pandas)
    • Machine Learning (Scikit-learn, XGBoost, Prophet / Greykite)
    • JavaScript (React / Hooks / TypeScript)
    • Databases (Postgres / Redis / DynamoDB)
    • Cloud (AWS - EC2, RDS, ECS, S3 / GCP / Azure)
    • CI/CD (AWS CodeBuild / GitHub Actions)
    • Containers (Docker / Kubernetes)
    • Data warehouses (Snowflake / BigQuery / Redshift / Presto / Synapse / DeltaLake)
Perks of working with us

👩‍💻 We were fully remote before it was a thing, your best work happens on your schedule
✈️ Unlimited vacation that we encourage you to take
🩹 Top of the line family-friendly medical, dental, and vision insurance plans
🍼 16 weeks paid maternity/paternity leave because family comes first
🔍 A radically open and transparent culture that supports autonomy and growth
💸 Meaningful employee equity packages plus life insurance and a 401k plan
🖥️ All new top-of-the-line laptops, monitors, and peripherals for doing your best work

What we value

Rational Optimism - We rely on each other to make principled decisions backed by data and logic
For & By All - Diverse, inclusive teams build better products that represent the needs of our customers
Own It - We champion ownership, and we take accountability for our work
Opacity Zero - Transparency enables our autonomous and fact-driven culture
Outcomes > Hours - People should work when and where they will be most productive
YOLO - Life's too short not to have fun at work