We're seeking an exceptional Senior Big Data & Machine Learning Engineer who will architect the future of our AI systems and drive technological innovation within our high-performing team.
What you'll be doing
As a key member of our AI team, you will:
Design Scalable Architecture – Architect, implement, and optimize robust ML pipelines that handle massive datasets with elegance and efficiency, from collection through preprocessing to production deployment
Pioneer Technical Solutions – Apply state-of-the-art machine learning technologies to solve complex challenges while maintaining the agility to incorporate emerging innovations
Drive Cross-Functional Excellence – Collaborate strategically with data scientists, software engineers, architects, and product leaders to transform advanced ML solutions into production-ready systems
What you'll be doing
As a key member of our AI team, you will:
Design Scalable Architecture – Architect, implement, and optimize robust ML pipelines that handle massive datasets with elegance and efficiency, from collection through preprocessing to production deployment
Pioneer Technical Solutions – Apply state-of-the-art machine learning technologies to solve complex challenges while maintaining the agility to incorporate emerging innovations
Drive Cross-Functional Excellence – Collaborate strategically with data scientists, software engineers, architects, and product leaders to transform advanced ML solutions into production-ready systems
Requirements:
Expert-level proficiency in Python, Java/Scala with demonstrable production experience
Advanced knowledge of streaming technologies such as Kafka or Kinesis
Mastery of big data processing frameworks including Apache Spark, Trino, Ray, or Dask Comprehensive experience with Data Lake management, including table formats (Iceberg, Delta, Hudi) and data warehouses (Redshift, BigQuery, Snowflake)
Proven expertise in workflow management systems (Airflow, Kubeflow, Argo)
Strong understanding of microservices architecture and event-driven design
Proven experience with huge volumes of data in production environments.
You might also have:
Cloud platform expertise across AWS, Google Cloud, or Azure, with containerization experience (Docker, Kubernetes)
Hands-on experience with ML frameworks including TensorFlow, PyTorch, and Scikit-Learn
MLOps proficiency including model registry management, experiment tracking (MLFlow, W&B), feature store management (Feast, Tecton), and serving platforms (Seldon Core, KServe, Ray Serve, SageMaker)
Experience with Vector Databases and Generative AI/Large Language Models
Basic knowledge of ML algorithms and data analysis techniques
Expert-level proficiency in Python, Java/Scala with demonstrable production experience
Advanced knowledge of streaming technologies such as Kafka or Kinesis
Mastery of big data processing frameworks including Apache Spark, Trino, Ray, or Dask Comprehensive experience with Data Lake management, including table formats (Iceberg, Delta, Hudi) and data warehouses (Redshift, BigQuery, Snowflake)
Proven expertise in workflow management systems (Airflow, Kubeflow, Argo)
Strong understanding of microservices architecture and event-driven design
Proven experience with huge volumes of data in production environments.
You might also have:
Cloud platform expertise across AWS, Google Cloud, or Azure, with containerization experience (Docker, Kubernetes)
Hands-on experience with ML frameworks including TensorFlow, PyTorch, and Scikit-Learn
MLOps proficiency including model registry management, experiment tracking (MLFlow, W&B), feature store management (Feast, Tecton), and serving platforms (Seldon Core, KServe, Ray Serve, SageMaker)
Experience with Vector Databases and Generative AI/Large Language Models
Basic knowledge of ML algorithms and data analysis techniques
This position is open to all candidates.
