
Senior AI Engineer
ZS.com
Hybrid
Status
Hexjobs Insights
Role: Senior AI Engineer. Responsibilities include developing AI pipelines, implementing IaC, leading a team, and optimizing models. Requirements: Bachelor's degree, 4+ years experience, proficiency in Python and AI libraries.
Schlüsselwörter
AI pipelines
machine learning
DevOps
Python
SQL
TensorFlow
PyTorch
cloud platforms
Docker
Kubernetes
Technologies we use
Your responsibilities
- Collaborate with data scientists, machine learning engineers, and DevOps teams to create robust, scalable, and reliable AI pipelines.
- Design, Develop and maintain automated processes for model training, deployment, and inference, ensuring best practices for model versioning, monitoring, and automated scaling.
- Implement infrastructure as code (IaC) principles to create reproducible AI environments and integrate AI pipelines into continuous integration and continuous deployment (CI/CD) workflows.
- Ensure seamless and secure deployment of AI models into production environments.
- Implement monitoring solutions to track model performance, detect data drift, and maintain data quality.
- Design and implement deep learning algorithms and neural networks for tasks such as image recognition, natural language processing (NLP), and speech recognition.
- Troubleshoot and optimize AI pipelines for efficiency, reliability, and compliance with industry standards (e.g., GDPR, HIPAA).
- Lead and mentor a team of junior AI Ops Engineers, providing technical guidance on AI Ops frameworks, deployment strategies, and observability.
- Foster a culture of continuous learning and innovation within the team, encouraging the exploration of new technologies and best practices.
- Collaborate with business stakeholders to understand AI project objectives and communicate progress and performance effectively.
Our requirements
- A relevant Bachelors or higher-education degree in Computer Science, Data Science, or related fields.
- Minimum of 4 years of professional experience in AI Ops, machine learning, and DevOps.
- Preferred certifications in AI, machine learning, and cloud platforms (e.g., AWS, Azure, GCP).
- Proficiency in Python, SQL, and relevant AI libraries (e.g., TensorFlow, PyTorch).
- Familiarity with cloud platforms (e.g., GCP, AWS) and containerization (Docker, Kubernetes).
- Strong problem-solving skills and ability to work in a collaborative environment.
- Proven track record of designing, implementing, and optimizing end-to-end AI pipelines.
- Demonstrated leadership experience, preferably leading small teams of engineers.
- Strong communications skills.
What we offer
Aufrufe: 8
| Veröffentlicht | vor 30 Tagen |
| Läuft ab | in etwa 7 Stunden |
| Arbeitsmodus | Hybrid |
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