Data Science Engineer (Python)

We are looking for a talented Data Scientist with expert Python skills and experience in processing large amounts of data to join our client’s team. You will be a key player in designing, building, and scaling our main data pipelines and ML systems. You will work closely with data scientists and engineers to create strong, efficient, and scalable systems.

Antenna is a remote‑first company; candidates must be able to work during US business hours and will report to the Data Science Lead.

What You’ll Do

• Design, develop, test, and maintain strong and scalable data pipelines using Python and tools for large‑scale data processing (such as Spark, Dask, or similar on GCP).
• Design and take ownership of key parts of our ML systems, ensuring they are reliable, efficient, and scalable.
• Set up and manage MLOps practices, including automatic updates for machine learning models (CI/CD), model monitoring, and automated launch plans.
• Improve and manage data processing jobs on cloud platforms (GCP: Dataproc, BigQuery, Cloud Run, Cloud Build).
• Work with data scientists to prepare machine learning models for production and connect them to our data systems.
• Write detailed documentation for system designs, code, and system management.
• Fix complex technical problems in distributed data systems and ML pipelines.

Who You Are

• 3‑5+ years of software engineering experience focused on data engineering, ML engineering, or building data‑intensive applications.
• Expert in Python, with strong object‑oriented and system design skills and experience building high‑quality, testable production code.
• Hands‑on experience with large‑scale data tools such as Apache Spark (PySpark), Dask, or similar.
• Solid experience with cloud platforms (GCP preferred). This includes deploying services, scaling them (e.g., Docker, Cloud Run, GKE), and working with large data systems (Dataproc, BigQuery).
• Strong SQL skills and experience working with large, complex datasets.
• Deep understanding of machine learning concepts, end‑to‑end model development, and MLOps principles.
• Excellent problem‑solving abilities, especially for troubleshooting distributed systems and improving performance.
• Clear and effective communication of complex technical ideas and system design decisions in English.
• Advanced English proficiency (B2‑C1) with strong communication, teamwork, and consulting skills.
• Passion for building robust, scalable systems and eagerness to mentor and collaborate with a team.
• Commitment to code quality, system reliability, and comprehensive documentation.

Bonus

• Experience or passion for the Subscription Economy, especially in media and entertainment.
• Deep knowledge of specific GCP services such as Dataproc, Dataflow, Cloud Composer, Vertex AI, or Kubernetes Engine.
• Experience building and maintaining widely used Python libraries or contributions to open‑source projects.
• Advanced knowledge of MLOps tools and workflow management (e.g., Cloud Build, Cloud Run).

Tech Stack

• Languages: Python (expert), SQL (strong)
• Large‑Scale Data Processing: Apache Spark/PySpark (or similar like Dask)
• Cloud Platform: Google Cloud (Dataproc, BigQuery, Cloud Storage, Cloud Run, Cloud Build, GKE)
• Version Control: Git (expert)
• MLOps & Orchestration: Tools such as Airflow, Kubeflow, Vertex AI Pipelines
• Containerization: Docker, Kubernetes
• Data Analysis Libraries: Pandas, NumPy (very proficient)
• Machine Learning: scikit‑learn, TensorFlow/PyTorch (production deployment experience)
• AI Tools: Claude, Gemini, OpenAI offerings