Machine Learning Infrastructure Engineer
hace 1 semana
We are a leading big data analytics provider for financial services, empowering our clients to enhance returns, reduce risk, and increase efficiency by integrating public information into their models and workflows.
Our team is responsible for building and maintaining the entire ML infrastructure, taking offline models and turning them into real production systems. We design and develop comprehensive test and monitoring strategies, implementing and maintaining the infrastructure in the cloud.
We are looking for a highly skilled MLOps Engineer to join our team, with a strong technical background and experience in implementing and optimizing data pipelines for ML workflows. The ideal candidate will have a proven track record in MLOps/DevOps or software automation projects and the ability to understand complex software solutions.
The successful candidate will have experience in all phases of the software development life cycle, from requirements gathering, designing CI/CD pipelines, integration testing, monitoring ML models performance, and supporting production systems. Excellent analytical, problem-solving, communication, and interpersonal skills are essential.
We offer a collaborative environment where we value your contribution, with ownership of projects and the opportunity to work with the latest technologies. As we encourage continuous learning, we will support your ongoing training.
Key Responsibilities:
- Implement and optimize data pipelines for ML workflows
- Design and implement CI/CD strategies
- Monitor ML models performance and support production systems
- Collaborate with QAs, ML, and DevOps engineers
Requirements:
- Experience in applying software engineering concepts and best practices to the entire machine learning development lifecycle
- Experience in implementing and optimizing data pipelines for ML workflows
- Experience in designing and implementing CI/CD strategies
- Familiarity with machine learning frameworks and understanding of machine learning concepts
- Proficiency in Python and knowledge in Scripting languages
- Database knowledge: SQL and NoSQL
Nice to Have:
- Experience setting and configuring monitoring and observability alerts
- Familiarity with QA processes
- Familiarity with LLMs model evaluation
- Familiarity with AWS services
What's in it for you:
- Work with the latest technologies
- Ownership of projects in a collaborative environment
- Opportunity to work in an agile environment with a fairly flat hierarchy
- Support for ongoing training and continuous learning
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