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Open nowFirst seen 33 hours ago

Sr Software Engineer – Machine Learning

T-mapp410 open roles

Where
Remote
Work mode
Remote
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Your applicationOpen nowSr Software Engineer – Machine LearningT-mapp · Remote

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The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market. T-mapp postings stay open a median of 1 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: first seen 33 hours ago

T-mapp median: 1 days open

The posting

Senior ML Engineer

About the Company

Our client is a technology company building advanced infrastructure powered by data, machine learning, and AI systems to solve complex problems at scale.

They are developing large-scale data pipelines, machine learning models, and agentic systems that enable automated workflows and intelligent decision-making. The team is focused on rapidly taking solutions from concept to production.

They are looking for a Senior Software Engineer who wants to work close to the core of the technology stack, building and operating robust AI/ML systems.

This position is open to candidates in: Colombia, Argentina, Brazil.

What will you do in this role?

You will be responsible for designing, building, and operating machine learning systems, large-scale data pipelines, and AI agents that power core product capabilities.

This role involves working across the full lifecycle of ML systems — from data ingestion and distributed processing to model deployment and monitoring.

Your main responsibilities will include:

  • Designing and building distributed data pipelines to process large datasets.
  • Developing and deploying machine learning models in production environments.
  • Implementing agent-based AI systems that interact with external services and internal infrastructure.
  • Designing scalable architectures for data processing and ML training pipelines.
  • Establishing observability for pipelines, models, and agents (metrics, tracing, alerting).
  • Evaluating modeling approaches and optimizing cost vs. performance trade-offs.
  • Collaborating with product and customer teams to build solutions that drive business impact.
  • Iterating quickly from prototype to production-ready systems.

This role requires strong technical ownership and the ability to build reliable systems end-to-end.

What should you bring?

We are looking for engineers with strong experience in production machine learning systems, distributed data processing, and scalable infrastructure.

Ideally you have:

  • Strong experience with Spark and SQL in distributed data environments.
  • Experience building and deploying machine learning systems in production.
  • Experience working with large and complex datasets.
  • Experience designing training, deployment, and monitoring pipelines for ML models.
  • Experience working with cloud services across data, compute, and ML.
  • Ability to design clear software architectures and well-documented systems.
  • Strong technical communication and collaboration skills.

Languages: Python, Scala

Tools / Frameworks: Spark, AWS (Sagemaker / Bedrock), Kubernetes

Nice to Have

  • Experience building products from 0 to production, especially in startup environments.
  • Experience working with large geospatial datasets and indexing strategies.
  • Experience building AI agents that operate at scale.
  • Experience with fine-tuning, distilling, or self-hosting LLM models.
  • Background in traditional ML with messy datasets and strong evaluation methodologies.
  • Experience with CI/CD, containerization, and infrastructure as code.

What you will receive

  • Contractor agreement
  • Compensation in USD
  • Fully remote work
  • Opportunity to work on cutting-edge AI and ML infrastructure
  • Highly technical environment with strong engineering ownership
  • The chance to build and scale systems that move from idea to production quickly

Submit your resume and join a process that can change your life.

Best regards, T-mapp Team

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