Senior Machine Learning Engineer

About The Role
In this role, you will help turn advanced machine learning ideas into reliable production solutions that deliver real business value. You will take ownership of building and scaling end-to-end ML systems while working within SoftServe’s AI and Data Science Center of Excellence, a community of more than 170 AI and ML specialists. Your work will connect applied research with production delivery through close collaboration with engineers, data scientists, and clients to create practical AI solutions with measurable impact
Responsibilities
Design end-to-end machine learning pipelines covering data ingestion, feature engineering, model training, optimization, and production deployment to support reliable AI solutions
Build and maintain LLMOps pipelines using experiment tracking and observability tools to improve model reproducibility, prompt management, and production visibility across ML systems
Collaborate with data scientists, engineers, and clients to transform business requirements into production-ready solutions for NLP, retrieval-augmented generation, and multimodal AI applications
Develop agentic systems and multi-agent workflows using frameworks such as LangGraph, CrewAI, or similar technologies to support autonomous AI capabilities at production scale
Enhance machine learning infrastructure by maintaining CI/CD/CT pipelines, cloud environments, data stores, monitoring processes, and security practices that support dependable operations
Integrate and package machine learning services into production applications while ensuring reliability, maintainability, and long-term operational stability
Operate workflow orchestration platforms such as Databricks Jobs and Workflows, Kubeflow, or Airflow to automate, schedule, and monitor machine learning pipeline execution
Requirements
Strong experience with building and deploying production-grade machine learning solutions, supported by at least three years of hands-on industry experience
Advanced knowledge of Python across the machine learning and data science ecosystem, including model development, packaging, and service integration
Hands-on expertise with LLMOps, AgentOps, and experiment tracking tools such as MLflow, Langfuse, LangSmith, and Weights & Biases
Solid understanding of CI/CD/CT practices for machine learning systems together with workflow orchestration platforms including Databricks Workflows, Kubeflow, or Airflow
Proven experience with cloud-based AI and machine learning services on AWS, Azure, or Google Cloud Platform
Working knowledge of agentic AI frameworks such as LangGraph, CrewAI, or similar technologies for building autonomous and multi-agent systems
Master’s degree in Computer Science or a related field
Strong communication skills with Upper-Intermediate or higher English proficiency, enabling effective collaboration with cross-functional teams and clients
SoftServe is an equal opportunity employer. Qualified applicants will receive consideration regardless of race, color, ancestry, ethnicity, national origin, religion, sex, sexual orientation, gender identity or expression, age, citizenship, disability, health condition, marital or family status, veteran status, or any other characteristic protected by applicable law.

Work arrangement
Yes