[Remote] Sr. Machine Learning Engineer

Note: The job is a remote job and is open to candidates in USA. Mirion Technologies is looking for a Sr. Machine Learning Engineer responsible for designing, building, and deploying machine learning systems for AI-driven features across their products. This role involves hands-on modeling, ML infrastructure work, and providing technical leadership while mentoring engineers and collaborating with stakeholders to create production-grade ML solutions.

Responsibilities

• Design, train, and deploy machine learning models for applied use cases across radiation safety, nuclear energy, and nuclear medicine
• Architect end-to-end ML systems, including training pipelines, model serving infrastructure, and monitoring
• Lead technical design reviews and mentor junior ML engineers on modeling, MLOps, and architectural best practices
• Establish standards for model evaluation, experiment tracking, reproducibility, and responsible AI across the team
• Partner with the Data Platform team to define feature requirements and ensure ML workloads are well-supported by the underlying data infrastructure
• Collaborate with stakeholders and product partners to translate business problems into well-scoped ML solutions
• Drive optimization initiatives for model performance, inference cost, and reliability in production
• Participate in hiring and team building for the Applied AI function
• Contribute to architectural decisions and long-term ML strategy
• Troubleshoot production model issues — drift, degradation, and pipeline failures — and implement robust monitoring and alerting

Skills

• 5+ years experience in machine learning engineering, applied ML, or related field
• Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, or similar)
• Deep experience taking ML models from research/prototype through to production deployment
• Hands-on experience with ML infrastructure — training pipelines, model serving, experiment tracking, and monitoring
• Solid software engineering fundamentals: testing, code review, version control, and CI/CD
• Working knowledge of SQL and modern data warehouses or lakehouses (Snowflake, BigQuery, Databricks, etc.)
• Experience with cloud platforms (AWS, GCP, or Azure) at scale
• Proven ability to mentor and guide junior engineers
• Experience building applied AI products or ML platforms from the ground up
• Experience with Databricks, MLflow, and lakehouse-based ML workflows
• Expertise with LLMs, RAG systems, or generative AI applications in production
• Experience with feature stores, vector databases, and real-time inference architectures
• Knowledge of model governance, model lineage, and responsible AI practices
• Background in regulatory-heavy industries or complex compliance requirements
• Experience with infrastructure-as-code and MLOps practices
• Background in computer vision, time-series, or signal processing (relevant to radiation detection data)

Company Overview

Company H1B Sponsorship