Role:

Machine Learning Engineer — Product AI/ML

Experience:

2-3 Years

Location:

Bangalore

Job Type:

Fulltime

Company Overview:

Cross Identity is a pioneer in Converged Identity and Access Management, acclaimed by top analysts across the globe. Our platforms have achieved the distinction of being the first Identity Fabric in the industry. Our technology is used in numerous countries and various industries, and we take pride in our continuous innovation and exceptional customer service.

Cross Identity now stands out for delivering two leading IAM solutions tailored for enterprise and small business customers. To support our exceptional growth, we are seeking smart, passionate, result-oriented, and hardworking professionals to join our team.

Website: https://www.crossidentity.com

About the role

We're hiring a Machine Learning Engineer to help build intelligent, data-driven features into our platform, starting with risk scoring for identity security. You'll design models that turn user activity data into meaningful risk signals — helping the product make smarter, more adaptive decisions instead of relying purely on static rules.

This is a foundational role: you'll help shape how ML gets used across the product going forward, not just execute a single fixed brief. As our AI/ML capabilities grow, so will the scope of what you own.

This is a security-adjacent, production ML role — your models will influence real decisions and actions within the product, so the people relying on them need to be able to trust and understand their output.

What you'll do

Design and build data pipelines that turn raw product/usage data into meaningful features for modeling.
Build models that produce clear, interpretable outputs that product and security teams can act on with confidence.
Prioritize interpretability and explainability — outputs should be understandable and defensible, not black-box.
Build the infrastructure to keep models updated as new data comes in, on both an event-driven and scheduled basis.
Work closely with backend and product engineers to integrate models into live product features.
Monitor models in production — track performance, flag drift, and iterate based on real usage and feedback.
Partner with product and engineering to identify other areas of the platform where ML/AI can meaningfully improve the product, and help scope and build those initiatives as our capabilities grow.

What we're looking for

2–3 years of experience building and deploying machine learning or data science solutions in a production environment — you've owned something end-to-end, not just built it in a notebook.
Strong Python skills and hands-on experience with common ML/data tooling (pandas, scikit-learn, NumPy, or similar).
Experience turning event or log-style data into engineered features — especially anything involving time windows, frequency counts, or recency-based signals.
Comfort with time-series concepts like decay functions, rolling averages, or trend detection.
A genuine preference for interpretable, explainable models over black-box complexity.
Experience working with APIs and integrating models into larger backend systems or products.
Strong communication skills — you'll need to explain modeling decisions to engineers, product managers, and non-technical stakeholders.

Nice to have

Background in security, fraud detection, anomaly detection, or trust & safety.
Exposure to anomaly detection techniques (supervised or unsupervised) for identifying unusual behavior patterns.
Experience with model monitoring or observability tooling in production.
Familiarity with regulated industries where automated decisions need to be auditable.

Why this role

You'll be one of the first dedicated ML hires at Cross Identity, building a capability from the ground up on a product with real customers and real stakes — not a side project or a proof of concept. There's real ownership here and real influence over what we build next as this function scales.

Job description