Machine Learning Expert

Global Tech & Capital Markets | Tel Aviv (Hybrid)

A global technology company in the capital-markets domain is seeking a Machine Learning Expert to join its ML/Quant group.

This is a high‑impact, hands-on role within a small, elite team responsible for building and deploying advanced ML-driven trading signals and data‑powered insights used across the company’s core products.

You will work closely with a global manager and collaborate with two additional ML engineers, contributing directly to the next generation of data, modeling, and signal‑generation infrastructure.

This position is ideal for someone who combines strong ML engineering fundamentals with curiosity for market data, experimentation, and production‑grade deployment.

Role Overview & Impact:

This role expands the team’s capacity to design, validate, and deploy sophisticated ML‑driven trading strategies.

You will help accelerate delivery, improve experimentation cycles, and strengthen the company’s higher‑tier product offerings.

You will work end‑to‑end - from data pipelines, feature engineering and modeling, to backtesting, packaging, and deployment.

Key Responsibilities:

Build and maintain complex SQL-based pipelines for modeling datasets

Design and execute large‑scale experiments with proper cross‑validation, leakage control, calibration, and reproducible backtesting

Develop ML models using state‑of‑the‑art techniques and deploy them into production environments

Perform feature engineering and preprocessing at scale

Build and package models for product integration using modern MLOps tools

Contribute to the planning and development of the Signals Engine MVP

(atomic signals, rule compiler, explanations)

Collaborate closely with ML/Quant stakeholders across regions

Job Requirements:

Python + production experience:

Pandas/Polars, SQL/BigQuery, FastAPI, Docker, CI/CD

Modeling expertise:

XGBoost / PyTorch, calibration, class imbalance handling, walk‑forward CV, leakage control

Experimentation at scale:

MLflow / DVC, reproducible backtests, GCP/Vertex jobs, orchestration frameworks

Capital markets:

Strong interest is required; understanding of equities/portfolio basics is important

(Algo‑trading experience is an advantage but not mandatory)

Nice to Have:

Familiarity with quirks of financial data and portfolio construction (typically the longest to master)

Experience from high‑caliber tech companies, fintech, trading, or data‑intensive startups

Role Structure:

Senior individual contributor

No people management

Full ownership across the ML lifecycle

Works closely with the ML/Quant team and global leadership

Location & Work Model:

Tel Aviv

Hybrid work environment

Let's Talk!