Remote ML Engineer — Real-Time Decisioning & Scale

Harnham; Austin (TX); Remote; USD 180,000 - 200,000; Full time

Benefits offered by this job

Bonus & equity

Fully remote (USA)

4-day workweek

Flexible PTO

Parental leave

Learning & development

Job summary

Harnham seeks a high-impact Machine Learning Engineer to build and scale production systems for real-time decisioning. You will join an AI Lab of 15 people and own end-to-end ML pipelines, delivering models that drive commercial outcomes at scale.

Collaborate with Product, Engineering, and Risk teams, deploy scalable pipelines in distributed environments (Spark), and translate business problems into robust ML solutions.

Qualifications

• Proven ability to build and deploy ML models from first principles.
• Experience with distributed computing environments (e.g., Spark).
• Strong Python and SQL for data processing and model development.
• Experience designing and running experiments rather than relying on pre-built models.
• Ability to translate business problems into scalable ML solutions.

Responsibilities

• Design and implement production-grade ML models for real-time decisioning.
• Build and optimise scalable ML pipelines to enable rapid experimentation.
• Explore and integrate new ML techniques to improve model accuracy and scalability.
• Collaborate with Product, Engineering, and Risk teams to deliver end-to-end solutions.
• Own projects end-to-end with accountability for production outcomes.

Skills

ML model deployment

Distributed computing (Spark)

Python

SQL

Experimentation design

Tools

Spark

Job description

Harnham seeks a high-impact Machine Learning Engineer to build and scale production systems for real-time decisioning. You will join an AI Lab of 15 people and own end-to-end ML pipelines, delivering models that drive commercial outcomes at scale.

Collaborate with Product, Engineering, and Risk teams, deploy scalable pipelines in distributed environments (Spark), and translate business problems into robust ML solutions.