MLOps Engineer

Our client a leading big data analytics provider for financial services, specializing in speed and accuracy in analyzing large amounts of unstructured content. Their products enable clients to enhance returns, reduce risk, and increase efficiency by incorporating public information into their workflows. Their clients include top hedge funds, banks, and asset managers worldwide.

We are seeking an MLOps Engineer to join the team responsible for building and maintaining the entire ML infrastructure. Your role will involve turning offline models into production systems and designing comprehensive test and monitoring strategies. You should have strong technical skills in cloud infrastructure implementation and maintenance, along with experience in MLOps/DevOps or software automation projects.

We are looking for a passionate software professional with a strong technical background. You will tackle challenges across the ML development lifecycle using the latest technologies.

Requirements

• Hands-on experience applying software engineering best practices to the ML development lifecycle, including deployments and monitoring.
• Proven track record optimizing data pipelines for ML workflows.
• Design and implementation experience with CI/CD strategies like AWS Sagemaker, Azure, or Vertex.
• Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and concepts.
• Proficient in Python and scripting languages for automation.
• Strong database skills in SQL and NoSQL.
• Ability to prioritize, multitask, and perform root cause analysis.
• Excellent analytical, problem-solving, and communication skills.
• Bachelor's degree in Computer Science or equivalent

Nice to have:

• Experience with monitoring and observability alerts.
• Familiarity with QA processes and LLMs model evaluation.
• Knowledge of AWS services and cloud infrastructure.
• Previous software development or architecture experience.

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