Middle Machine Learning Engineer
Listed on 2026-06-03
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IT/Tech
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Overview
In this role you will build and maintain end-to-end ML systems — from data pipelines and model training to LLMOps tooling and agentic workflows — as part of Soft Serve’s AI and Data Science Center of Excellence. Working alongside 170 experienced ML engineers, data scientists, and architects, you’ll contribute to cutting-edge NLP, RAG, and multimodal AI projects that deliver real impact for clients.
Responsibilities- Implement and maintain end-to-end ML pipelines supporting data ingestion, feature engineering, model training, and deployment into production environments
- Build and support LLMOps pipelines using tools such as MLflow, Langfuse, or Lang Smith, contributing to model observability, reproducibility, and prompt versioning across projects
- Collaborate with Data Scientists, Senior Engineers, and stakeholders to understand requirements and contribute to production-ready ML solutions for NLP, RAG systems, and multimodal models
- Contribute to the development of agentic systems and multi-agent workflows using frameworks such as Lang Graph or CrewAI, supporting autonomous AI applications
- Support and improve ML infrastructure tasks, including CI/CD pipelines, cloud environments on AWS, Azure, or GCP, data stores, and monitoring tooling
- Integrate and package ML services into real applications, writing clean, maintainable code that meets engineering and quality standards
- Configure and maintain workflow orchestration pipelines using tools such as Kubeflow, Airflow, or Databricks Workflows
- At least 2 relevant years of hands-on experience building and deploying ML solutions, with exposure to Cloud production environments
- Solid Python proficiency across the data science and ML ecosystem, including model development and basic service integration
- Familiarity with LLMOps and experiment tracking tools such as MLflow, Langfuse, or Lang Smith
- Understanding of CI/CD practices for ML systems and workflow orchestration tools such as Kubeflow, Airflow, or Databricks Workflows
- Experience with cloud-based AI/ML services on AWS, Azure, or GCP
- Basic knowledge of agentic AI concepts and frameworks, such as Lang Graph or CrewAI
- Master’s degree in Computer Science or a related field
- Upper-intermediate or higher proficiency in English, both spoken and written
Soft Serve is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment regardless of race, color, religion, age, sex, nationality, disability, sexual orientation, gender identity and expression, veteran status, and other protected characteristics under applicable law. Let’s put your talents and experience in motion with Soft Serve.
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