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Strong experience with building and deploying production-grade machine learning solutions, supported by at least three years of hands-on industry experience
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Advanced knowledge of Python across the machine learning and data science ecosystem, including model development, packaging, and service integration
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Hands-on expertise with LLMOps, AgentOps, and experiment tracking tools such as MLflow, Langfuse, LangSmith, and Weights & Biases
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Solid understanding of CI/CD/CT practices for machine learning systems together with workflow orchestration platforms including Databricks Workflows, Kubeflow, or Airflow
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Proven experience with cloud-based AI and machine learning services on AWS, Azure, or Google Cloud Platform
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Working knowledge of agentic AI frameworks such as LangGraph, CrewAI, or similar technologies for building autonomous and multi-agent systems
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Master’s degree in Computer Science or a related field
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Strong communication skills with Upper-Intermediate or higher English proficiency, enabling effective collaboration with cross-functional teams and clients
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Design end-to-end machine learning pipelines covering data ingestion, feature engineering, model training, optimization, and production deployment to support reliable AI solutions
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Build and maintain LLMOps pipelines using experiment tracking and observability tools to improve model reproducibility, prompt management, and production visibility across ML systems
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Collaborate with data scientists, engineers, and clients to transform business requirements into production-ready solutions for NLP, retrieval-augmented generation, and multimodal AI applications
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Develop agentic systems and multi-agent workflows using frameworks such as LangGraph, CrewAI, or similar technologies to support autonomous AI capabilities at production scale
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Enhance machine learning infrastructure by maintaining CI/CD/CT pipelines, cloud environments, data stores, monitoring processes, and security practices that support dependable operations
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Integrate and package machine learning services into production applications while ensuring reliability, maintainability, and long-term operational stability
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Operate workflow orchestration platforms such as Databricks Jobs and Workflows, Kubeflow, or Airflow to automate, schedule, and monitor machine learning pipeline execution
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SoftServe University, with learning opportunities, certification support and leadership opportunities to help you grow your skills
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Medical insurance for you and your family
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Food vouchers
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Extra days off
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Dare to Care, our holistic well-being program
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Anniversary Program to celebrate your time with us
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