GE
GetinzAI/ML Engineer
Innovation Engineer responsible for AI - driven solutions at a digital commerce company. Focused on prototyping, exploring technologies, and shaping technology strategy.
About the role
- Design and build ML infrastructure and applications to support design, deployment, and monitoring of ML pipelines and models
- Ensure 100% uptime and bulletproof fault-tolerance of ML platform components
- Process thousands of energy data points per second from diverse operational sources and run real-time classification and anomaly detection models
- Maintain comprehensive data lineage and model governance for production systems
- Collaborate with software engineers, data scientists, energy analysts, and traders to bridge research experiments and production systems
- Deliver high-performance platforms and actionable predictions (equipment failure detection, demand forecasting, anomaly identification, predictive maintenance, optimization recommendations)
- Validate model quality with in-house energy analysts, traders, and domain experts
Requirements
- Experienced in building and deploying distributed scalable ML pipelines that can process large volumes of energy data daily using Kubernetes and MLflow
- Solid machine learning engineering fundamentals
- Fluent in Python
- Experience with PyTorch
- Experience with XGBoost
- Skilled in developing classification models and anomaly detection systems for production environments
- Capable of implementing comprehensive data lineage tracking and model governance systems
- Driven by working in an intellectually engaging environment with energy analysts, traders, and technology experts
- Excited about working in a dynamic environment and bringing ML innovations to production
- Passionate about mentoring team members
- Experienced with the full ML model lifecycle: experiment design, model development, validation, deployment, monitoring, and maintenance
- (Nice to have) Experience in the energy sector or understanding of energy systems and operations
- (Nice to have) Practical experience with AWS services (SageMaker, S3, EC2, Lambda, etc.)
- (Nice to have) Experience with infrastructure as code tools (Terraform, CloudFormation)
- (Nice to have) Experience with Apache Kafka and real-time streaming frameworks
- (Nice to have) Familiarity with observability principles such as logging, monitoring, and distributed tracing for ML systems
- (Nice to have) Experience with transformer architectures and generative AI applications in operational contexts
- (Nice to have) Experience with time series analysis and forecasting techniques relevant to energy applications
- (Nice to have) Knowledgeable about data privacy regulations and compliance frameworks in the energy sector
Benefits
- Enjoy flexible hybrid working – split your time between home and our office, with the freedom to work where you’re most productive.
- A vibrant, diverse company pushing ourselves and the technology to deliver beyond the cutting edge
- A team of motivated characters and top minds striving to be the best at what we do at all times
- Constantly learning and exploring new tools and technologies
- Acting as company owners (all Vortexa staff have equity options)– in a business-savvy and responsible way
- Motivated by being collaborative, working and achieving together
- Private Health Insurance offered via Vitality to help you look after your physical health
- Global Volunteering Policy to help you ‘do good’ and feel better
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
Tech skills
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