Machine Learning Engineer
VARTEQ Inc.
Salary:
Gross salary
$4500 - 7500
Type:
Full time
Tags: Python Machine Learning Deep Learning AWS SageMaker
We are VARTEQ Inc., a remote-first IT outsourcing and product company with teams across the US, Europe, and LatAm. We build scalable, data- and AI-driven solutions for clients in fintech, edtech, and enterprise software. In this long-term, actively growing engagement, we support enterprise B2B clients across the US and Europe—including manufacturing, distribution, and high-tech—by building and integrating complex digital commerce solutions on platforms such as SAP, Salesforce, and Shopify. We are looking for a Machine Learning Engineer to help design, build, and optimize production-ready ML systems, with a specific focus on recommender systems for large-scale business impact.
Apply only from getonbrd.com.
Your Responsibilities:
We are technology consultancy teams working with enterprise B2B clients across the US and Europe. In this role, we focus on delivering production-ready machine learning capabilities.
- Design, build, and optimize machine learning models for production use, with a focus on recommender systems.
- Develop and maintain scalable ML pipelines, including data processing, training, evaluation, and deployment.
- Work with large datasets to extract insights and improve model performance.
- Collaborate with cross-functional teams to integrate ML solutions into production systems.
- Continuously improve model performance through experimentation, tuning, and monitoring.
- Ensure reliability and scalability of ML systems in cloud environments.
Qualifications:
We are looking for an experienced Machine Learning Engineer with strong production ML and MLOps experience.
- 5+ years of hands-on experience in machine learning engineering.
- Strong proficiency in Python and core ML frameworks such as PyTorch, TensorFlow, scikit-learn, and XGBoost.
- Solid experience with deep learning, including model architecture, training, and optimization.
- Proven experience designing and deploying recommender systems.
- Hands-on experience with AWS SageMaker and the broader AWS ML ecosystem.
- Practical experience building and maintaining data pipelines and ML workflows.
- Experience working with production ML systems and MLOps practices.
We also value teammates who are proactive in monitoring model health, rigorous about reliability and scalability, and comfortable collaborating across engineering and product stakeholders to ensure ML solutions work end-to-end in production.
Desirable:
- Experience with experimentation frameworks, A/B testing, and offline-to-online evaluation for recommender systems.
- Familiarity with model monitoring approaches (e.g., drift detection, performance tracking) and incident response for ML in production.
- Good understanding of data versioning and reproducible training workflows.
- Experience integrating ML outputs into business-facing systems and improving user-facing recommendations over time.
What We Offer
- 100% remote, async-friendly culture
- Flexible working hours
- Competitive compensation (contract-based)
- Direct collaboration with US-based clients
- English-speaking environment
- Paid time off + public holidays
We also support an international team with clear processes, and we offer paid vacation, holidays, and sick leave.
Fully remote
You can work from anywhere in the world.
Flexible hours
Flexible schedule and freedom for attending family needs or personal errands.
Computer provided
VARTEQ Inc. provides a computer for your work.
Source: GetOnBoard | Main Category: Other