---
title: 'Senior Engineering Manager, Machine Learning at Signifyd'
canonical: 'https://feeny.ai/job/senior-engineering-manager-machine-learning-signifyd-united-states-hps6avfdnyv8'
type: 'job'
last_seen: '2026-09-05'
---

# Senior Engineering Manager, Machine Learning at Signifyd

- **Company:** Signifyd
- **Location:** United States
- **Work type:** remote
- **Posted:** 2026-08-14
- **Last confirmed live:** 2026-09-05
- **Apply:** https://job-boards.greenhouse.io/signifyd95/jobs/8126825

## Job description

At Signifyd, we help merchants confidently grow their businesses by building trusted relationships with their customers. Our advanced technology, combined with a team genuinely invested in our clients’ success, creates frictionless shopping experiences, approving more good orders, protecting revenue, and keeping customers happy.

Trusted by thousands of leading merchants across more than 100 countries, we securely process billions of transactions each year. Our people are the heart of everything we do, driving our mission forward with commitment, empathy, and creativity. Join us on our mission to empower confident, fraud-free commerce by helping online retailers provide superior customer experiences and eliminate fraud. Learn about our company values [here](https://www.signifyd.com/about/#values)!

Signifyd AI Lab (SAIL) builds the ML products behind Signifyd's fraud and risk decisions. We improve the predictive performance of the models that decide e-commerce transactions at scale, we scale the ML capabilities of our Risk organization, and we push into the new markets and problem spaces that expand the market Signifyd can sell to.

Every space in this department is a mix of experimentation, code, and statistics.  We don't create walls between the people who have the ideas and the people who build them. The team splits its time between near-term continuous model improvements and longer-horizon innovation bets to improve the company’s capabilities in 2027 and beyond.  These bets surface from the ground up in an environment where we believe those closest to the problems are best placed to understand how to solve them.

We’re hiring a manager to lead one of the teams in this department.

## Who You Are

You are a hands-on Player-Coach manager who thrives in ambiguity—where the roadmap is a set of hypotheses, and the answer to "will this work?" is "we'll know in three weeks."

You bring:

Technical Credibility (The "Player"): You stay close enough to the work to have a grounded opinion. You read the code, inspect evaluation pipelines, and can immediately tell the difference between a statistical result that will hold up in production and one that just happened to look good on a single test window.

Leadership & Rigor (The "Coach"): You hold a high bar for evidence without becoming a bottleneck to experimentation. You mentor engineers to own their code quality, and you translate complex ML performance metrics into clear business outcomes for Risk leadership.

Executive Judgment: You know how to balance research bets against quarterly delivery, disagree and commit when decisions are made, and build an environment where well-documented negative experimental results are celebrated as real progress.

## What You'll Do

Lead and grow the team

- Guide career development, manage conflicts, and nurture a positive work environment.
- Develop career plans with team members, provide guidance on skill development, and follow up on their evolution.
- Engage in regular 1:1s, give constant feedback, and create a safe environment for open discussion — including the discussions that follow an experiment that didn't work.
- Set clear goals, mentor the team, and foster a collaborative environment across a geographically distributed organization.
- Encourage a culture of learning and improvement, provide technical guidance, and support team members in both technical and soft skills.
- Conduct technical and hiring-manager interviews, train the team on interviewing techniques, and help us keep raising the bar as we grow.
- Identify and address gaps in team capabilities and processes to enhance team efficiency and success.

Run a portfolio of experiments, not a delivery queue

- Partner with your tech leads, who own and drive the technical roadmap for their areas. Your job is not to be the sole source of ideas — it is to pressure-test them, sharpen them, make sure the strongest ones get resourced, and make sure the people generating them have the room and the support to do it. When you do bring an idea, you bring it as a peer in the technical conversation.
- Make the calls the roadmap can't make for you: which hypotheses get compute and headcount, which get another iteration, and which get a clear, documented "no." A well-run negative result is a real outcome, and we treat it as one — but only if it's declared, written down, and learned from.
- Manage the trade-off between a committed improvement target you must hit this year and research bets that may not pay off for several quarters. You will re-cut that budget as evidence arrives, and you'll be able to explain the reasoning to both your team and your stakeholders.
- Bring rigor to how the team decides something worked. Offline results have to predict online behavior; a strong point estimate on a single evaluation window is a starting point, not a conclusion. You will be the person asking whether the improvement survives a rolling evaluation, whether it's already captured by a change we shipped last month, and what would have to be true for it to be wrong.
- Own delivery on a cadence. Independent experimental workstreams have to converge into a release candidate, get evaluated end to end, and ship — including the hard call to leave a workstream out of a release when it isn't carrying its weight.

Set direction from data, in partnership with Risk

- Work directly with our Risk partners as your primary stakeholders. Our commitments to them are explicit, measured, and written down; we deliver model performance, and they own thresholds, rules, and how decisions are applied to merchants.
- Operate with a high degree of autonomy. Our direction comes from measured performance against those commitments and from what our own experiments tell us, not from a product backlog handed to the team. You are expected to know what your team should be working on and to defend it, rather than wait to be told.
- Partner with our platform and infrastructure engineering teams on the feature systems, training pipelines, and experimentation tooling your team depends on — and be clear about where the boundary sits between what SAIL should own and what belongs to Engineering.
- Represent your team's results to a broad audience: engineering leadership, Risk leaders, and the wider company.

## What You'll Need

- Roughly 5+ years in machine learning, data science, or ML-adjacent software engineering, including at least 3 years of people management — guiding career development, addressing conflicts, and building a healthy, high-performing team.
- Genuine depth in at least one of engineering and applied statistics, and real working competence in the other. We are not hiring a manager of analysts, and we are not hiring a manager of a pure software team. Our engineers train production models that decide serious traffic, and we expect their manager to be able to engage with that work at a technical level.
- Demonstrated ability to lead work under real uncertainty: setting a direction when the answer isn't known yet, changing course when evidence says to, and communicating both without eroding your team's confidence.
- Excellent written and verbal communication. Much of our decision-making happens in documents, and we expect managers to write well.
- Autonomy in recognizing priorities and evaluating the impact of outcomes, and comfort working without close supervision in a fast-moving environment.
- Commitment to quality. You take pride in work that excels in correctness, reproducibility, and reliability, and you set that standard for your team.

#LI-Remote

Benefits in our US offices:

- Discretionary Time Off Policy (Unlimited!)
- 401K Match
- Stock Options
- Annual Performance Bonus or Commissions
- Paid Parental Leave (12 weeks)
- On-Demand Therapy for all employees & their dependents
- Dedicated learning budget through Learnerbly
- Health Insurance
- Dental Insurance
- Vision Insurance
- Flexible Spending Account (FSA)
- Short Term and Long Term Disability Insurance
- Life Insurance
- Company Social Events
- Signifyd Swag

Compensation:

In the United States, each work location is assigned a specific pay zone, which determines the salary range for a given position. The starting base salary for the selected candidate will be based on a variety of factors, including job-related skills, experience, qualifications, geographic location, and current market conditions.

Base Salary Ranges by Pay Zone:

- Tier 1 (NYC/SF Bay Area/Seattle): $220,000 – $245,000 annually
- Tier 2 (DC Metro/Austin/Chicago/Denver/Boston/Los Angeles/San Diego): $210,000 – $235,000 annually
- Tier 3 (US - All Other): $200,000 – $225,000 annually

Equity: This role is eligible for a stock option grant of 5,000 stock options, based on the position level and internal compensation guidelines.

Bonus: This role is eligible for an annual performance bonus of up to 10% of base salary. [Signifyd's Applicant Privacy Notice](https://drive.google.com/file/d/1HSnMY6HGjB1FNRX4Ez9bUre5mrPPcHIq/view?usp=sharing)

## About Signifyd

## Company Overview
- **One-liner**: Signifyd provides an end-to-end Commerce Protection Platform that leverages machine learning to guarantee merchants against fraud and consumer abuse, offering a 100% financial guarantee on shipment decisions.  
- **Entity Type**: Private (venture‑backed)  
- **Headquarters**: San Jose, California, USA  
- **Founded**: Not publicly available on the company site  
- **Founders**: Mike Liberty and Rajesh Ramanand (Co‑Founder & CEO)  

## Core Business
- **Primary industry**: E‑commerce fraud prevention and chargeback guarantee  
- **Target customers**: Online retailers of all sizes (B2B, B2C, enterprise, SMB)  
- **Mission / purpose statement**: “Empower friction‑free commerce – friction‑free customer experience without worry about fraud and consumer abuse.”  

## Products & Services
- **Commerce Protection Platform** – SaaS platform that uses machine learning and the Commerce Network to provide real‑time ship/don’t‑ship decisions with a 100% financial guarantee against fraud.  
- **Guaranteed Fraud Protection** – Flags risky orders and covers chargebacks if a fraudulent order is approved.  
- **Policy Abuse Prevention** – Detects and prevents abuse of return policies, promotion abuse, and unauthorized reselling.  
- **Return Fraud & Abuse Protection** – Identifies patterns of fraudulent returns.  
- **SCA Optimization** – Solutions to optimize checkout under Europe’s Strong Customer Authentication requirements.  
- **Financial Services Solution** – Extends fraud‑prevention technology to banks and other financial institutions.  

## Market Standing
- **Valuation / Market Cap**: Not publicly disclosed.  
- **Key Metric (Private)**: Total funding amount not available in provided sources; backed by a strong syndicate of investors.  
- **Notable Investors / Partners**: Premji Invest, Bain Capital Ventures, Menlo Ventures, American Express Ventures, IA Ventures, Allegis Cyber, Resolute Ventures.  
- **Growth Signals**:  
  - Sales increased 7% YoY in 2024.  
  - Fraud pressure (risky orders) rose 20% YoY in 2024.  
  - Consumer abuse increased 23% YoY in 2024.  
  - Named the leading provider of payment security and fraud prevention for e‑commerce’s largest brands by Digital Commerce 360 for four consecutive years.  
  - Recognized as one of the 10 Most Innovative Companies in AI by Fast Company.  

## Competitive Advantages
- **100% financial guarantee** – If Signifyd approves an order that later results in a chargeback, Signifyd covers the loss, removing risk for merchants.  
- **Large Commerce Network** – Machine learning model is trained on data from thousands of stores and hundreds of millions of transactions, improving accuracy.  
- **End‑to‑end coverage** – Protects against fraud, policy abuse, return fraud, promo abuse, and unauthorized reselling.  
- **SCA compliance** – Built‑in solutions for European authentication mandates.  

## Strategic Focus
- **Expansion into financial services** – Bringing fraud‑prevention innovation to banks and other financial institutions.  
- **International growth** – Offices in Mexico City, São Paulo, Belfast, London, Budapest, Denver, and New York.  
- **Continuous AI improvement** – Investment in machine learning and AI to stay ahead of evolving fraud tactics.  

## Why Work Here
- **4‑day workweek** – All employees benefit from a reduced workweek.  
- **Remote‑first** – Remote work available to all employees; offices in multiple cities for those who prefer hybrid.  
- **Competitive compensation** – Cash + equity, generous parental leave (birth, adoption, surrogacy), on‑demand therapy, and an annual Learnerbly stipend for professional development.  
- **DEI focus** – Company‑wide requirement for diverse interview panels, semi‑annual gender pay equity audits, annual budgets for Employee Resource Groups, and a monthly DEI speaker series.  
- **Engineering culture** – Top‑flight engineering team constantly improving machine learning technology; transparent career ladders and individual development plans.  
- **Culture recognition** – Recognized by Forbes, Entrepreneur, Silicon Valley Business Journal, and Inc. Magazine for workplace culture.  

## Sources
1. [signifyd.com/about](https://www.signifyd.com/about/)  
2. [signifyd.com/careers](https://www.signifyd.com/careers/)  
3. [boards.greenhouse.io/signifyd95](https://boards.greenhouse.io/signifyd95)  
4. [signifyd.com/life-at-signifyd](https://www.signifyd.com/life-at-signifyd/)  
5. [signifyd.com/jobs](https://www.signifyd.com/jobs/)

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