Machine Learning Engineer
Sao Paulo,
Brasil
At Olyra, we're redefining how businesses operate by designing and deploying AI Agents that automate intelligent tasks and optimize business processes. We help mid-market and enterprise clients integrate AI into their daily operations—not just as a tool, but as a transformative partner. Join us if you’re ready to help shape the future of automation, one AI Agent at a time.
Job Purpose (What You’ll Do)
Machine Learning Engineer – AI Agent Intelligence & Model Integration
As a Machine Learning Engineer at Olyra, you will design, fine-tune, and implement models that enhance the intelligence, accuracy, and adaptability of our AI Agent solutions. You’ll work closely with AI developers, automation engineers, and solution architects to ensure models can operate in real-time environments, integrate with business systems, and continuously improve through feedback loops. Your work will support agents that not only complete tasks—but learn from outcomes, adapt to business logic, and make data-driven decisions that deliver measurable ROI.
Responsibilities
- Develop, train, and deploy custom or fine-tuned machine learning models used within multi-agent systems and AI-driven workflows
- Integrate LLMs (e.g., OpenAI, Claude, LLaMA) and specialized models into agent infrastructure, ensuring accuracy, performance, and compliance
- Build data pipelines for training, inference, and continuous learning from user interactions, structured logs, or CRM/ERP systems
- Implement vector databases, embeddings, and memory architectures to enhance agent recall and contextual awareness
- Collaborate with AI Agent Developers to translate business logic into decision models, classification tasks, or recommendation systems
- Monitor model performance in production environments and lead tuning, retraining, or replacement as needed
- Apply MLOps principles to maintain scalable, secure deployment pipelines for model lifecycle management
- Work with DevOps to optimize compute environments (Docker, GPU/CPU scaling, cloud deployment) for performance and efficiency
Must Have
- 3+ years of experience building and deploying machine learning models in production environments
- Proficiency in Python, including ML libraries such as scikit-learn, TensorFlow, PyTorch, or XGBoost
- Experience working with LLMs or NLP models and embedding/vector-based search systems (e.g., FAISS, Weaviate, Pinecone)
- Strong understanding of supervised and unsupervised learning, model evaluation, and performance tuning
- Familiarity with API-driven integration and data pipelines (REST APIs, JSON, ETL frameworks)
- Ability to work cross-functionally in a fast-paced, remote-first environment with asynchronous collaboration
- Valid work permit for the country you will work from
Nice to have
- Experience fine-tuning or augmenting LLMs (OpenAI, Claude, Mistral, etc.) for business-specific applications
- Background in conversational AI, agent reasoning, or multi-model coordination for real-time decision support
- Exposure to data sources commonly found in mid-market business environments (CRM, ERP, unstructured inputs)
- Familiarity with MLOps tools such as MLflow, Kubeflow, ClearML, or model registries
- Knowledge of data governance, privacy, and compliance standards relevant to AI deployments in Brazil, the U.S., or Brazil
What's great in the job?
- Great team of smart people, in a friendly and open culture
- No dumb managers, no stupid tools to use, no rigid working hours
- No waste of time in enterprise processes, real responsibilities and autonomy
- Expand your knowledge of various business industries
- Create content that will help our clients on a daily basis
- Real responsibilities and challenges in a fast evolving company
What We Offer
Each employee has a chance to see the impact of their own work.
You can make a real contribution to the success of the company.
Several activities are often organized all over the year, such as team building events, monthly social, and much more
Perks
A full-time position
Attractive salary package
Flexibility in time & locations.
Training
12 days / year, including
6 of your choice.
You make an Impact
Be valued and appreciated,
for your contributions. We listen
to our team to grow as a company.
Online & In Person
Social events to build
team relationships.