Bigabid focuses on solving the key challenge of growth for mobile apps by building Machine Learning and Big Data-driven technology that can both accurately predict what apps a user will like and connect them in a compelling way.
Our technology operates at a scale well beyond many of the largest Internet companies, processing over 50 TB of raw data per day, handling over 4 million requests per second, and interacting with over a billion unique users a week.
Our innovative platform is leading-edge with a strong product-market fit. As a result, we're seeing remarkable growth and close to zero customer churn. To support our hyper-growth and continue propelling the growth of some of the biggest names in the mobile industry, we offer a wide range of opportunities for different skill levels and experiences.
We are looking for an ML Engineer / MLOps Tech Lead to promote machine learning engineering excellence. Someone who is passionate about building scalable, high-quality data products and processes, while ensuring production systems maintain strong real-time performance observability.
You will focus on designing and maintaining the core infrastructure that empowers the Machine Learning Engineers working within Data Science product teams. You’ll collaborate closely with stakeholders across data science, product, and engineering, playing a pivotal role in driving the business by architecting and enabling the infrastructure for machine learning model development, serving, and lifecycle management—the foundation of our product.
Responsibilities:
- Collaborate with product, data science, and engineering teams to solve complex problems, identify trends, and create opportunities through robust ML infrastructure.
- End-to-end ML delivery – enabling model performance development, training, validation, testing, and version control.
- Build and support monitoring and observability tools – dashboards, alerts, and performance tracking of models in production.
- Lead architecture projects such as: Feature Store, Vector / Graph Databases.
- Data wrangling – supporting and enabling data requirements for research, training, validation, and testing.
- Drive engineering best practices including code and model versioning, CI/CD pipelines, rollout strategies, and disaster recovery procedures.
- 3+ years of experience as an ML Engineer / MLOps
- 5+ years of experience as a software engineer or data engineer
- 2+ years of experience in a technical leadership role (leading engineers or data scientists)
- Strong programming skills in Python and SQL
- Hands-on experience with MPP frameworks such as Spark, Flink, Ray, Dask or equivalent
- Strong analytical and critical thinking skills
We are looking for a Machine Learning Tech Lead to promote machine learning engineering excellence. Someone who is passionate about building scalable, high-quality data products and processes, while ensuring production systems maintain strong real-time performance observability
