Senior Ml Engineer
hace 2 semanas
**Senior ML Engineer**:
- Colombia,Costa Rica,Medellín, Antioquia,Bogotá, Capital District,Cali, Valle del Cauca,Barranquilla
**About project**
As a Senior ML Engineer at Provectus, you'll be responsible for designing, developing, and deploying production-grade machine learning solutions for our clients. You will work on complex ML problems, mentor junior engineers, and contribute to building ML accelerators and best practices.
**Core Responsibilities**:
- 1. Technical Delivery (60%)
- Design and implement end-to-end ML solutions from experimentation to production
- Build scalable ML pipelines and infrastructure
- Optimize model performance, efficiency, and reliability
- Write clean, maintainable, production-quality code
- Conduct rigorous experimentation and model evaluation
- Troubleshoot and resolve complex technical challenges
- 2. Collaboration and Contribution (25%)
- Mentor junior and mid-level ML engineers
- Conduct code reviews and provide constructive feedback
- Share knowledge through documentation, presentations, and workshops
- Collaborate with cross-functional teams (DevOps, Data Engineering, SAs)
- Contribute to internal ML practice development
- 3. Innovation and Growth (15%)
- Stay current with ML research and emerging technologies
- Propose improvements to existing solutions and processes
- Contribute to the development of reusable ML accelerators
- Participate in technical discussions and architectural decisions
**Requirements**:
- Comfortable with standard ML algorithms and underlying math.
- Strong hands-on experience with LLMs in production, RAG architecture, and agentic systems
- AWS Bedrock experience strongly preferred
- Practical experience with solving classification and regression tasks in general, feature engineering.
- Practical experience with ML models in production.
- Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines.
- Solid software engineering skills (i.e., ability to produce well-structured modules, not only notebook scripts).
- Python expertise, Docker.
- English level - strong Intermediate.
- Excellent communication and problem-solving skills.
**Will be a plus**:
- Practical experience with cloud platforms (AWS stack is preferred, e.g. Amazon SageMaker, ECR, EMR, S3, AWS Lambda).
- Practical experience with deep learning models.
- Experience with taxonomies or ontologies.
- Practical experience with machine learning pipelines to orchestrate complicated workflows.
- Practical experience with Spark/Dask, Great Expectations.
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