ML/AI Engineer
Quick Summary
Are you looking to thrive in a stimulating work environment? Join Levio , a leader in digital transformation, and take your career to the next level.
Join Levio, a leader in digital transformation, and take your career to the next level. You will work alongside high-caliber professionals on ambitious, large-scale technology projects, directly embedded in our clients’ environments. At Levio, we value expertise, curiosity, and continuous improvement — and we give you the space to grow.
About the Role
~1 min readThe ML / AI Engineer design, build, deploy, and operate production-grade machine learning and generative AI systems. This role owns the end-to-end ML lifecycle, ensuring models and AI services are scalable, reliable, secure, and deliver measurable business value. The role will be remote.
What We Offer
~1 min readResponsibilities
~1 min read- →Design, implement, and productionize machine learning and generative AI models
- →Build training, validation, and inference pipelines for ML and LLM-based solutions
- →Implement feature engineering, embeddings, and model versioning best practices
- →Support LLM-based systems, including RAG architectures and inference optimization
- →Implement CI/CD for ML and LLM workflows, including automated deployment and rollback
- →Monitor AI systems for performance, drift, bias, and reliability in production
- →Optimize compute usage, latency, and operational costs across AI workloads
- →Ensure AI systems comply with security, privacy, and responsible-AI standards
- →Collaborate with AI Architects, Developers, and Data Engineers across delivery teams
- →Mentor junior ML/AI engineers and contribute to engineering best practices
Requirements
~1 min read- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field
- 6+ years of experience in engineering roles, with 3+ years in AI/ML positions
- Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn)
- Hands-on experience deploying and operating ML models in production
- Experience with cloud ML platforms, especially AWS SageMaker
- Strong understanding of data pipelines, model lifecycle management, and monitoring
Location & Eligibility
Listing Details
- Posted
- July 10, 2026
- First seen
- September 23, 2026
- Last seen
- September 23, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 22%
- Scored at
- September 23, 2026
Signal breakdown
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