Machine Learning Engineer
About the Role
Join DataFlow Systems as a Machine Learning Engineer and help build scalable ML pipelines that power real-time decision-making for Fortune 500 clients. You'll design and implement ML models, optimize inference performance, and collaborate with data engineers to ensure robust data pipelines.
We offer a fully remote work environment with flexible hours, competitive compensation, and the opportunity to work on cutting-edge problems in recommendation systems, anomaly detection, and natural language processing.
Responsibilities
- Design and implement ML models for production systems
- Optimize model inference performance and scalability
- Build and maintain ML pipelines and data infrastructure
- Collaborate with data engineers on data quality and availability
- Conduct experiments and iterate on model architectures
Qualifications
- 4+ years of experience in machine learning engineering
- Proficiency in Python, PyTorch or TensorFlow
- Experience with MLOps tools (MLflow, Kubeflow, or similar)
- Strong understanding of distributed computing
- Experience deploying models to production at scale
Preferred
- MS or PhD in Computer Science, Statistics, or related field
- Experience with NLP and recommendation systems
- Contributions to open-source ML projects
Benefits
◆Why This Role Fits TPA Candidates
Role requires understanding of AI systems and capabilities
Process-oriented approach to AI integration
Practical experience with AI-powered automation
Clear communication about AI capabilities and limitations
This is an external opportunity curated by Prompt Academy.
Applications through Prompt Academy follow Prompt Academy screening standards.
Certification does not guarantee interview or offer.
AI proficiency screening required for Prompt Academy channel
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Prompt Academy is not the employer. This role is an external opportunity that has been curated and verified by our team.
About DataFlow Systems
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