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Senior Software Engineer - Machine Learning

2 hours, 9 minutes ago
Poland, Romania, Argentina, Brazil, Colombia, Turkey
Full-time
Senior
AI Engineer
Software Development
Apache Spark CI/CD Kubernetes LLM Machine Learning Python SageMaker Scala SQL
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PartnerOne

PartnerOne

PartnerOne specializes in enterprise software solutions that manage extensive data environments through hyper automation, virtualized cloud storage, artificial intelligence, and metadata analytics, serving many of the world's largest corporations.

Media
51-250
View All Jobs 28

Description

  • Own the end-to-end AI/ML lifecycle, from data ingestion and distributed processing through model development, deployment, and monitoring.
  • Work with complex, messy data and evaluate multiple approaches to deliver robust, production-ready models.
  • Design and implement large-scale agent-based systems with access to external systems and integrate them into existing infrastructure.
  • Build operational ML/AI solutions with attention to cost-versus-performance tradeoffs.
  • Establish observability for pipelines, models, and agents, including metrics, tracing, and alerting.
  • Collaborate with product and customer teams to support revenue-driving work and deliver customer impact.
  • Contribute to geospatial data pipelines directly or by applying AI to improve them.
  • Iterate quickly from initial concept to deployed solution in a production environment.

Requirements

  • Strong experience with distributed data processing, especially Spark and SQL.
  • Proven expertise building production machine learning systems, including training, deployment, and monitoring.
  • Experience designing and deploying task-oriented AI agents and working with coding agents.
  • Experience working with cloud services across data, compute, and ML.
  • Strong communication skills, including code architecture and documentation that support team troubleshooting and contribution.
  • Proficiency in Scala and Python.
  • Experience with Spark, AWS SageMaker/Bedrock, and Kubernetes.
  • Preferred: startup experience or growing projects from 0 to production in a larger organization.
  • Preferred: experience with large geospatial datasets, formats, and indexing strategies.
  • Preferred: experience building operational AI agents at scale, including millions of complex tasks such as web research.
  • Preferred: experience with fine-tuning, distilling, and self-hosting LLMs.
  • Preferred: traditional ML experience with messy data and robust model evaluation.
  • Preferred: experience with CI/CD, infrastructure as code, and containerization.

Interested in this position?

Apply directly on the company website

Apply Now

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