Senior MLOps Engineer (with Back-end experience) (вакансія неактивна)

Binariks is looking for a highly motivated Senior MLOps Engineer on the part-time basis as a contractor or a consultant. The project is about a marketing technology system for Investment and e-commerce to streamline investors to relevant investment opportunities.

What We’re Looking For

• 3+ years of hands-on experience as an MLOps or ML Engineer with ops orientation.
• Proven track record in building and managing ML pipelines, CI/CD processes, and tools.
• Extensive experience in ML workflows and Data Orchestration frameworks such as AirFlow, Prefect, MLFlow, Kubeflow, SageMaker, etc.
• Familiarity with container orchestration tools, including Kubernetes.
• Experience with cloud-based services.
• Ability to write efficient, scalable Python code.
• Experience with source control (e.g., Bitbucket, Git).
• Strong problem-solving skills with good analysis for root cause detection.
• Ability to work both collaboratively with a team and independently.
• Self-learner with a can-do attitude.

Will be a plus

• Node.js Nest.js
• Helicone long-chain, custom model experience, on-edge model experience
• Inference of models in the browser to minimize latency
• GCP
• Vertex, LLAMA custom deploy
• OLAMA experience

Your Responsibilities

• Build the infrastructure for the ML lifecycle, from development to deployment and monitoring.
• Work together with Data Scientists, Data Engineers, Software Engineers, and Product teams to train, deploy, and manage ML models throughout their lifecycle — from development to production.
• Design, implement, manage, monitor, and optimize a scalable and robust infrastructure for machine learning workflows.
• Implement metrics-based processes to improve the accuracy and reliability of our ML models, including early detection and mitigation of performance issues.
• Implement and manage CI/CD pipelines for machine learning workflows.
• Automate model training, retraining, testing, validating, and deployment processes.
• Proactively identify and resolve issues related to model performance and data quality.
• Communicate effectively with stakeholders to understand requirements and provide