Machine Learning Engineer

POSITION: Machine Learning Engineer

# LOCATION: Remote (San Antonio, Detroit, New Orleans)

HOURS: Full-Time, Non-Union. 40hrs/week

COMPENSATION: $110k - $130k (Commensurate with Experience)

ABOUT THE POSITION

As a Machine Learning Engineer, you will build production foundations that allow our machine learning capabilities to run reliably at scale across the US and UK. This role focuses on the engineering required to operationalize machine learning — including low‑latency serving, API integration, data pipelines for inference, monitoring, and robust deployment practices — so that model outputs can be activated in customer‑facing channels.

You will deliver the real‑time serving layer that connects our data platform (e.g., Snowflake) with activation platforms such as Iterable. You will design and maintain the architecture, services, and workflows that move us from offline modelling to always‑on personalization, supporting CRM first and expanding to other channels over time.

PEOPLE, PLACES, AND THINGS

- Contribute to designing, scaling/building, evaluating, integrating, and refining machine learning models.
- Collaborate with Marketing and Engineering across the US and UK to define how machine learning underpins personalized customer communications.
Build reusable science infrastructure, design and build production-grade measurement systems and establish robust evaluation frameworks.

EXPERIENCE AND SKILLS

Essential

• 3+ years’ experience as an ML Engineer delivering production ML systems (models + pipelines) at scale.
• Degree in a quantitative field in Computer Science, Machine Learning, Operations Research (or equivalent technical background with demonstrated impact).
• Proficient in Python and modern ML tooling, with solid software engineering practices (testing, packaging, code quality).
• Hands‑on experience with AWS and cloud-native patterns (e.g., Lambda, S3, IAM/security, event-driven architectures, monitoring).
• Experience designing inference architectures (batch + low‑latency / near‑real‑time), including storage, caching, queues/streaming, and performance tuning.
• Familiar with orchestration and data pipelines for features/inference (e.g., Airflow) and modern data stacks (e.g., Snowflake/dbt), including API-based integrations.
• Familiar with MLOps foundations: model/version management, feature stores, monitoring/drift, and production experimentation (A/B assignment, logging, guardrails).
• Bonus: experience activating ML outputs in customer engagement platforms (e.g., Iterable) and real-time personalization patterns

BENEFITS

• Medical, Dental and Vision Insurance
• 401k Match
• Paid Vacation & Holidays

ATG Entertainment: Passion Behind Performance

ATG Entertainment is a world leader in live entertainment. Our portfolio of venues includes historic theatres, studio theatres, cinemas, conference spaces, and modern live music arenas. ATG Entertainment own, operate or program 64 of the world’s most iconic venues across the UK, the US and Germany entertaining over 18 million audience members each year.

ATG Entertainment: IDEA Mission Statement

At ATG Entertainment, our commitment to inclusion, diversity, equity, and access (IDEA) is reflected in our IDEA mission statement: A stage for everyone. Our stages are a platform for compelling stories – stories that are for all, by all, and of all. We shine our spotlight on our differences and believe that understanding and celebrating these differences makes us better global citizens. We are committed to strengthening the sense of belonging by ensuring diversity and equity in everything we do. We strive to make our venues beacons of these ideals in our communities. Onstage and off, we hold ourselves accountable for nurturing an inclusive culture, one in which everyone can bring their authentic selves, and everyone feels they belong. At ATG Entertainment, we provide a stage for everyone.