Senior Machine Learning Engineer

🕒 May 5

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Globaldev Group

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 12 years

🤝 B2B

☁️ SaaS

🏢 Enterprise

B2B • SaaS • Enterprise

Globaldev Group is an international company that specializes in providing IT outsourcing and software development services. They focus on assisting businesses in building and managing their engineering teams, offering expertise in various modern technologies and development practices to ensure efficient and effective project delivery.

📋 Description

• Lead and drive the deployment, lifecycle management, and monitoring of ML/DL models in all stages leading to production. • Design and implement systems for Dataset and Label Management, including versioning and integrating customer feedback into labeling workflows. • Establish and maintain a robust Model Repository/Registry that supports versioning, local inference, and model lineage. • Lead the implementation of advanced Experiment Tracking and Monitoring solutions for both Data Science and Generative AI, focusing on evaluation, data drift detection, and model reproducibility. • Own model serving and inference systems—including autoscaling, A/B testing, canary rollouts, and latency/cost optimization for production models. • Enable specialized infrastructure for Generative AI capabilities, including tagging tools, prompt management, and LLM testing services. • Drive operational excellence by improving tool deployment usability and implementing granular cost visibility across projects and environments. • Developing reusable components such as standardized data loaders, CI/CD pipelines, and automated workflows for tasks like model retraining. • Collaborate directly with Data Scientists and the rest of the Data Platform Engineering team to productionize ML/DL models developed for cloud environments.

🎯 Requirements

• B.Sc. or M.Sc. in Computer Science or Software Engineering or related field • Experienced with ML/DL workflows and their best practices • Experienced with CI/CD workflows and their best practices • Worked with public cloud (AWS/Azure/GCP) • Experienced with Python and Java • Experience with various data stores like Postgres, MongoDB, Redis • Experience with DS tools such as MLFlow, Langfuse, SageMaker, etc. • Experience with Spark • Experience with PyTorch/TensorFlow

🏖️ Benefits

• Flexible work arrangements. • 15 working days per year as Non-Operational Allowance for personal recreation, fully compensated. • Health insurance. • Public holidays. • Truly competitive salary. • Supportive HR and management team.