Senior Machine Learning Engineer
TechifideLast week
- Where you can work from
- Remote — Brazil onlyBrazil
- Salary
- Salary not disclosedThe employer did not publish a range. We do not estimate one.
- Job type
- Full-time
- Experience
- Senior
Skills
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via Himalayas · Himalayas
Job description
Future opportunities / Brazil / Remote
We're building our network of exceptional Senior Machine Learning Engineers based in Brazil for upcoming opportunities with international technology companies.
AI and machine learning engineering is currently one of the areas where we're seeing the highest demand from our clients. While this application is not tied to a specific open position, we're interviewing strong candidates now so that we can move quickly when suitable roles become available.
The opportunities we typically work on involve building production AI systems at scale, using advanced machine learning, large language models and intelligent automation to solve complex, real-world problems.
What you could be working on
- Building and developing AI platforms involving search, retrieval and multi-agent orchestration.
- Designing and implementing multi-agent architectures, defining how specialist agents interact to solve complex tasks.
- Designing, building and optimising large-scale document processing pipelines, including ingestion, parsing, chunking, indexing and structured data extraction.
- Improving search and retrieval capabilities through ranking, query understanding and AI-powered question answering.
- Building and maintaining knowledge graphs and other graph-based systems to improve reasoning and retrieval.
- Taking ownership of high-impact AI projects from concept and experimentation through to production.
- Developing evaluation frameworks and experimentation processes to measure model performance and continuously improve quality.
- Writing clean, scalable, production-ready code and contributing to strong engineering practices.
About you
We're interested in experienced engineers who enjoy solving difficult technical problems and turning AI research and experimentation into reliable production systems.
You'll ideally have
- 7+ years of experience designing, building and deploying production-grade machine learning or AI systems.
- A proven ability to lead technically challenging projects with meaningful business impact.
- Strong experience building LLM-powered applications, AI agents or orchestration frameworks.
- Deep knowledge of document processing pipelines, including parsing, chunking, indexing and structured information extraction.
- Experience working with distributed systems and technologies such as Kubernetes.
- Knowledge of knowledge graphs, provenance graphs or similar graph-based data models.
- Strong software engineering skills in Python, Go or similar languages.
Experience in one or more of the following areas is particularly relevant:
- Search and ranking systems
- Natural Language Processing (NLP)
- Recommendation systems
- Large-scale ML infrastructure
Experience within construction, engineering, AEC or other document-intensive industries is also valuable.
Why apply now?
We're interviewing engineers in Brazil now to build a shortlist for future international opportunities.
By completing our process in advance, we'll already understand your technical background, experience, English level and career goals. When a suitable opportunity becomes available, we can contact you directly and potentially move much faster through the hiring process.
If you're an experienced Machine Learning Engineer based in Brazil and interested in working remotely with international technology companies, we'd like to hear from you.
Originally posted on Himalayas
Job availability & source
Still listed on the employer's own board at our last check, 16 hours ago
This job was originally posted by the employer or source shown below. We re-check the original listing regularly to keep its availability current, and send you straight to it to apply — we never sit in between.
- Source
- Himalayas
- Posted by the employer
- 16 Oct 2026
- First seen by us
- 16 Oct 2026
- Last checked
- 25 Oct 2026
via Himalayas — view on source
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