Sr Machine Learning Engineer
Build and deploy ML models from scratch (e.g., Random Forests, Neural Networks) to detect spam and threats, using Python and cloud infrastructure without managed services.
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Ml / AI
- Posted
Skills
Must have
- Strong understanding of machine learning algorithms, statistics, feature engineering, and optimization
- Hands-on experience building and deploying ML models using Python
- Experience in trust and safety/spam detection, analyzing data for threat identification
- Proficiency in setting up and managing cloud infrastructure for model deployment
Nice to have
- Working knowledge of Natural Language Processing (NLP)
- Familiarity with LLM tooling — prompt engineering, embeddings, and vector databases
- Experience with Scikit-Learn, TensorFlow, PyTorch, Pandas, NumPy, NLTK, spaCy
- Experience with AWS/Azure or similar cloud platforms
- Experience with Django or Flask for API deployment
Full description
THIS OPENING IS AVAILABLE FOR CANDIDATES IN LATIN AMERICA, NOT LIMITED TO ONLY COLOMBIA.
Sonatafy Technology, headquartered in Scottsdale, Arizona, is an award-winning nearshore software development company with a strong reputation. They have a dedicated in-house team of engineers, offering end-to-end software solutions and supporting client development staff augmentation. Catering to companies of all sizes and industries, including some of the world's largest brands, Sonatafy Technology is a trusted provider of nearshore enterprise-level cloud and mobile application software development services.
Responsibilities
- Design and build machine learning models from scratch using algorithms such as Decision Trees, K-Means, Neural Networks, and Random Forests.
- Deploy machine learning models manually using Python, ensuring scalability, reliability, and performance.
- Analyze data points such as IP addresses, locations, and user behavior to identify patterns related to spam detection and trust/safety.
- Perform feature engineering and selection to build effective machine-learning models.
- Set up and manage cloud infrastructure to deploy machine learning models without relying on managed services such as Amazon SageMaker.
- Innovate and experiment with solutions independently, taking ownership of complex problems without constant supervision.
Skills and Qualifications
- Strong understanding of machine learning algorithms, statistics, feature engineering, and optimization.
- Hands-on experience with building and deploying machine learning models using Python.
- Experience in trust and safety/spam detection, analyzing data for threat identification.
- Proficiency in setting up and managing cloud infrastructure for model deployment.
- Independent problem-solver with a creative and experimental mindset.
- Working knowledge of Natural Language Processing (NLP).
- Familiarity with LLM tooling — prompt engineering, embeddings, and vector databases, among others.
Technical Tools:
- Machine Learning Libraries:Scikit-Learn, TensorFlow, PyTorch.
- Data Manipulation:Pandas, NumPy, NLTK, spaCy.
- Cloud Infrastructure:AWS and/or Azure, or similar cloud platforms.
- Web Frameworks for API Deployment:Django or Flask for building APIs to serve machine learning models in production.
Why Work with Sonatafy?
At Sonatafy, you'll join a community of highly skilled engineers across Latin America supporting innovative U.S.-based teams. You’ll be part of a fast-moving, client-first culture where your code has real-world impact. We offer competitive compensation, a remote-first lifestyle, and career growth opportunities across industries and technologies.