Senior ML Engineer
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Job Description
Own and operate recommendation systems for a high-scale B2B marketing platform. Contributing to ML systems, enhancing consumer data processing with direct revenue impact.
Responsibilities:
- Own the client's recommendation system end-to-end: design, training, deployment, and monitoring
- Build and mature ranking and retrieval models that process behavioral signals — clicks, opens, purchases — at consumer scale
- Operate ML systems at hundreds of millions of events per day, with direct impact on client revenue
- Make independent technical decisions and engage directly with client engineering leadership — no intermediaries
Requirements:
- 6 to 9 years of experience in software or data engineering roles
- 4+ years building and operating ML systems in production
- 2 to 3+ years with recommendation systems as a core area of work — not adjacent exposure
- Hands-on experience with ranking and retrieval architectures; able to discuss tradeoffs from real production work
- Direct experience operating systems at consumer scale (hundreds of millions of events per day or more)
- Strong Python skills and fluency with a modern ML stack: PyTorch or TensorFlow, scikit-learn, feature engineering libraries
- SQL fluency for data exploration and validation
- Production deployment experience on AWS, GCP, or Azure
- Fluent spoken and written English — this role involves direct technical conversation with US client engineering leaders
- Demonstrated autonomy in client or stakeholder-facing settings: owning scope, raising blockers, making independent decisions.
Benefits:
- 100% remote from Argentina, Brazil, Mexico, or Colombia
- Paid certifications: AWS, GCP, Azure, Databricks, dbt
- English classes included
- Extra week of vacation + birthday off
- Annual team trip
- Referral bonus
- Monthly credits on Maslow benefits marketplace
- Direct engagement with a US-based enterprise client. Remote from LATAM.
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