Senior ML Engineer developing scalable production ML systems across various teams in JobCloud. Leading innovation in the AI - driven recruitment landscape, improving job ad visibility and performance.
About the role
- MLOps Engineer responsible for designing and maintaining ML pipelines at JobCloud. Collaborating with teams to productionize ML models and ensuring robust system performance.
Responsibilities
- Design, build, and maintain end-to-end ML pipelines from data ingestion to model deployment and monitoring
- Collaborate with data scientists and cloud engineers to productionize ML models and establish best practices
- Develop and maintain model serving infrastructure with focus on scalability, reliability, and low latency
- Manage ML experiment tracking, model versioning, and model registry systems
- Monitor model performance in production and implement alerting systems
- Implement security best practices for ML systems and ensure compliance with data governance policies
- Document MLOps processes, architecture decisions, and runbooks.
Requirements
- Bachelor's degree or higher in Computer Science, Data Science, Engineering or related field
- 5+ years of experience in MLOps, DevOps, or related production ML roles
- Experience deploying ML/AI prototypes into production
- Excellent communication skills and ability to work cross-functionally
- Self-motivated with ability to work independently and manage multiple priorities
- Passion for automation and building reliable systems
- Detail-oriented with focus on code quality and best practices
- Hands-on experience with modern ML frameworks (PyTorch, TensorFlow, or similar)
- Familiarity with LLM frameworks, vector databases, and RAG architectures
- Strong experience with cloud platforms (AWS, GCP, or Azure)
- Experience with cloud data warehouses, SQL/NoSQL databases and real-time data pipelines
- Hands-on experience with container orchestration (Kubernetes, ECS, or similar)
- Proficiency with CI/CD pipelines, Infrastructure as Code, and version control
- Strong understanding of REST API design and implementation.
Benefits
- 25 days of annual vacation leave plus 10 days of fully paid sick leave.
- Fringes benefits: meal allowance, work-from-home allowance, gym allowance, private health insurance plan for yourself and 2 children.
- 1 day per month to tackle challenges inside the project, or test new ideas.
- Tech training and human skills training and, budget for conferences.
- Opportunity to travel and collaborate in our various office locations for workshops or team-building events.
- A dynamic work environment that highly fosters a sense of fun while maintaining a productive atmosphere.
- A competitive salary.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Senior Machine Learning Engineer at greehill developing ML solutions for sustainable urban living. Leading projects in Computer Vision and Deep Learning to transform urban environments.
Machine Learning Engineer developing deep learning models for self - driving vehicle systems at BlueSpace.ai. Engage in innovative ML applications while collaborating with a seasoned team in the autonomous vehicle ecosystem.
Machine Learning Engineer developing perception foundation models leveraging multimodal sensor data for autonomous vehicles at Woven by Toyota. Design, implement machine learning solutions, influence Toyota production vehicles.
Senior ML Engineer developing and scaling multitemporal, multimodal models for Earth observation using satellite imagery at LiveEO. The role involves applied research and engineering with real - world impacts.
Senior Machine Learning Engineer developing deep learning models for radiological imaging applications. Focusing on designing and validating ML solutions to support accurate medical diagnoses with interdisciplinary teams.
Senior Machine Learning Engineer involved in speech - to - text projects at Level AI. Designing ASR systems and collaborating in a fast - paced AI environment.
Senior MLOps Engineer at dLocal building and operating ML and AI platform. Focus on Feature Store and automation in MLOps workflows.
Principal Machine Learning Engineer driving technical direction for core Snap products. Set vision and develop ML technology for millions of Snapchatters.
Senior Machine Learning Engineer designing and developing generative AI systems for Adobe Firefly Services. Collaborating with other engineering teams on innovative solutions and optimizing performance in large - scale environments.