ML Engineer

SoftServe is a global digital solutions company that delivers outcomes through digital expertise and innovation. The AI and Data Science Center of Excellence serves as a hub for AI/ML development, covering the full lifecycle from problem framing to deployment, with a focus on Generative AI and Agentic AI systems.

• Work on ML applications involving NLP, RAG systems, and multi-modal models;
• Design and implement end-to-end ML pipelines from data infrastructure to model optimization;
• Build LLMOps pipelines for model observability, reproducibility, and prompt versioning;
• Design and develop agentic systems and orchestrate multi-agent workflows;
• Collaborate with clients to gather requirements and translate them into production-ready ML solutions;
• Partner with Data Scientists and Engineers to support the full ML lifecycle;
• Productize large language models and other advanced AI models;
• Enhance and support ML infrastructure including CI/CD, cloud setup, data stores, monitoring, and security;
• Act as a consultant and tech expert on projects.

• Master’s degree in Computer Science or a related field;
• 3+ Years of experience building and deploying real-world machine learning solutions;
• Hands-on production experience with Databricks;
• Proficiency in Python and the core data science and machine learning ecosystem;
• Experience developing, packaging, and integrating ML services into applications;
• Ability to design and implement robust ML pipelines;
• Familiarity with cloud-based AI/ML services on AWS, Azure, or GCP;
• Knowledge of CI/CD/CT practices for machine learning;
• Experience with MLflow, Langfuse, LangSmith, and Weights & Biases;
• Knowledge of workflow orchestration tools like Databricks Jobs/Workflows, Kubeflow, or Airflow;
• English at an upper-intermediate level or above;
• Nice to have: Interest in autonomous AI systems, familiarity with decision-making algorithms, planning frameworks, or agentic tools like LangGraph and CrewAI.

• Access to world-class training and cutting-edge research;
• Opportunities for international events and professional certifications;
• Access to educational and mentorship programs;
• Supportive work environment.