Staff Machine Learning Engineer

phantom· Engineering
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🌍 Remote📍 RemoteFullTime

About this role

Phantom is on a mission to connect the world to the freedom of open markets. Tens of millions of people all over the world use Phantom to access global markets that never close, including perpetuals, prediction markets, tokenized assets, stablecoins and memes. Phantom users are able to discover the markets that matter and the cultural moments that shape them, building conviction through real-time data and the verified performance of top traders. With self-custody and access to open networks at its core, Phantom lets them control their financial moves in the same app they use to safely store or spend money worldwide.

Phantom has reached #1 in Google Play's finance category and consistently ranks in the top 50 apps across all categories. Phantom partners with many of the most trusted and influential names in finance like Hyperliquid, Stripe, Kalshi and Visa, to make the most popular and innovative financial products accessible to everyone.

We are around 180 people, fully remote, backed by a $150M Series C investment from a16z, Sequoia Capital and Paradigm.

Role Overview

We are seeking a visionary and hands-on Staff Machine Learning Engineer to lead the technical strategy, architecture, and execution of our Growth and Engagement ML initiatives. In this role, you will bridge the gap between advanced machine learning and business strategy, designing systems that drive user acquisition, retention, lifetime value (LTV), and deep product engagement.

As a technical pillar of the engineering organization, you will own the end-to-end lifecycle of complex ML models, mentor senior engineers, and collaborate closely with Product, Data Science, and Marketing leadership to move core business metrics.

Key Responsibilities

Technical Leadership & Strategy

  • Define the long-term technical roadmap for Growth and Engagement ML systems, ensuring scalability, reliability, and measurable business impact.

  • Architect and deploy production-grade ML pipelines and real-time decisioning systems that power personalization, notification dispatch, and onboarding flows.

  • Evaluate and integrate cutting-edge ML techniques, including multi-armed bandits, reinforcement learning, LLMs for content generation, and advanced graph neural networks.

Execution & Modeling

  • Design, train, and validate sophisticated models targeting user lifecycle stages: propensity to churn, lifetime value (LTV) forecasting, next-best-action, and lookalike modeling.

  • Build and optimize recommendation engines and semantic search systems to surface highly relevant content, products, or features to users.

  • Establish robust experimentation frameworks (advanced A/B testing, causal inference, and multi-variate testing) to rigorously validate model variants in production.

Collaboration & Mentorship

  • Partner with Product and Growth marketing teams to translate high-level business hypotheses into precise, actionable machine learning problems.

  • Mentor and coach senior engineers across the data and ML organizations, fostering a culture of technical excellence and continuous learning.

  • Advocate for ML engineering best practices, including model monitoring, feature store utilization, reproducible training pipelines, and data governance.

Qualifications & Skills

Experience

  • 8+ years of professional experience in machine learning engineering, data science, or software engineering, with at least 3+ years in a Staff, Principal, or Tech Lead capacity.

  • Proven track record of building and scaling ML systems specifically within growth, marketing tech, recommendation engines, or consumer engagement domains.

  • Extensive experience with large-scale data processing and distributed computing.

Technical Proficiencies

  • Languages: Expert-level Python, Scala, or Java.

  • ML Frameworks: PyTorch, TensorFlow, JAX, or XGBoost.

  • Data & MLOps Infrastructure: Spark, Flink, Kafka, Snowflake/BigQuery, Ray, Kubeflow, MLflow, or SageMaker.

  • Experimentation: Deep understanding of causal inference, uplift modeling, and robust statistical testing methodologies.

Core Competencies

  • Business Acumen: Ability to directly connect algorithmic improvements to top-line growth metrics (e.g., MAU/DAU, conversion rates, retention curves).

  • Communication: Exceptional ability to explain highly complex technical architectures and algorithmic choices to non-technical stakeholders and executives.

Why Work with Us

Opportunity

We are a team of experienced builders with a ton of traction in a big and growing market – our users are so passionate they were hacking their way into our private beta. We've acquired millions of users in our 3+ years and are adding more every week! On top of that, there has never been a better time to work in crypto and on wallets in particular.

  • Wallets play a pivotal role: Wallets are responsible for on-boarding new users into crypto, and can make or break the user experience.

  • We are moving to a multi-chain world: New blockchains and scaling solutions are coming online and gaining traction, but are lacking decent wallets and bridges.

  • DeFi & NFTs are exploding : Interest in DeFi and NFTs has exploded, yet they are still an after-thought in existing wallets.

Benefits

  • Competitive salary and equity

  • Comprehensive insurance (medical/dental/vision) 100% covered

  • Stipend for your ideal remote / WFH set-up: laptop, headphones, and any other work gear you may need

  • Flexible hours and a long-standing, supportive remote environment

  • Unlimited vacation: Take time when you need it (and we really mean it!)

  • 401(k) retirement plan

  • Wellness benefit

  • Daily lunch benefit

We strongly encourage candidates of all backgrounds to apply. We believe that our work is stronger with a variety of perspectives, and we’re eager to further diversify our company. If you have a background that you feel would make an impact at Phantom, please consider applying. We’re committed to building an inclusive, supportive place for you to do the best work of your career.

By submitting your resume and application materials, you acknowledge and agree that Phantom Technologies, Inc. ("Phantom") collects and processes your personal information (including application materials, interview records, and related data) to evaluate your candidacy. Phantom may use AI-powered tools and third-party service providers for transcription, note-taking, scheduling, and other administrative tasks. Phantom does not sell your information and your materials will be handled securely and in accordance with applicable data protection laws.

Frequently Asked Questions

Is the salary disclosed for the Staff Machine Learning Engineer position at phantom?
The salary for this Staff Machine Learning Engineer role at phantom is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Is the Staff Machine Learning Engineer job at phantom remote?
Yes, this Staff Machine Learning Engineer position at phantom is remote, with team members based in Remote. You can work from home or anywhere in the supported regions.
Is the Staff Machine Learning Engineer role at phantom full-time or part-time?
This is listed as a FullTime position. It is posted as a Staff Machine Learning Engineer role in the Engineering department at phantom.
Which team or department does the Staff Machine Learning Engineer at phantom belong to?
This Staff Machine Learning Engineer position is part of the Engineering department at phantom. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Staff Machine Learning Engineer position at phantom?
Click the "Apply Now" button on this page. You will be redirected to phantom's official application portal hosted on ashby where you can submit your application directly.
When was the Staff Machine Learning Engineer job at phantom posted?
This Staff Machine Learning Engineer position at phantom was posted on Sep 14, 2026. Apply as soon as possible — early applications are often reviewed first.
Staff Machine Learning Engineer
phantom
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