Senior Machine Learning Engineer page is loaded## Senior Machine Learning Engineerremote type: In Officelocations: Cork Irelandtime type: Full timeposted on: Posted Todayjob requisition id: R46960 C.
H.
Robinson is seeking a Senior Machine Learning Engineer to help build robust, scalable systems that empower our data science and engineering teams.
As a Machine Learning Engineer, you will play a key role in delivering production‑grade, scalable ML infrastructure and services.
You'll collaborate directly with scientists and engineers across product teams to iterate on user needs, deliver intelligent capabilities, and optimize performance.
You'll also help build and maintain a reusable platform that accelerates the machine learning lifecycle: from experimentation to deployment and monitoring.
In this role, you will also contribute to new predictive and data‑driven capabilities that enhance our customer‑facing technology.
You'll bring strong machine learning expertise, a proactive problem‑solving mindset, and the ability to translate problem statements into effective ML strategies.
Your work will directly support our teams in building meaningful, high‑impact solutions used across our platform ecosystem.**Responsibilities**The duties and responsibilities of this position consist of, but are not limited to, the following:* Collaborate with data scientists, product engineers, and stakeholders to design, implement, and technically lead ML‑powered solutions* Build and maintain reusable libraries, pipelines, and platform tools that enable efficient model training, deployment, and monitoring* Contribute to evolving our domain models and ontology layer that supports consistent data and ML integration* Iterate with users to ensure solutions are intuitive, performant, and aligned with their workflows* Apply software engineering best practices, including secure coding, modular design, and CI/CD automation* Write comprehensive unit and performance tests to ensure system stability and prevent regression* Proactively identify and resolve technical debt, performance bottlenecks, and scalability challenges* Document systems and code for maintainability and team‑wide knowledge sharing* Stay current with industry best practices in MLOps, cloud computing, and ML system design**Required Qualifications*** Bachelor's or Master's degree in Computer Science, Engineering, or a related field* 5+ years of experience in software engineering or machine learning engineering* Experience in the logistics/supply chain industry or with a company where building software solutions is a core part of the business (e.g., product‑driven environments, technology‑led organizations, or companies with strong supply‑chain or data‑heavy operations)* Proficiency in Python and C#/.
NET Core for backend and ML‑integrated workflows* Strong experience with Azure ML, Azure Cloud Services, and containerized environments (Kubernetes)* Experience designing and building scalable data or ML pipelines using tools like Airflow/Astronomer* Familiarity with data platforms such as Snowflake, Postgre SQL, Mongo DB, and Redis* Solid understanding of distributed systems, microservices, and message‑based architectures (e.g., Kafka)* Proven experience writing production‑level code with attention to testing, logging, and monitoring**Preferred Qualifications*** Demonstrated experience leading end‑to‑end delivery of production ML systems or platform components* Experience implementing and scaling MLOps practices in a production environment* Hands‑on experience working with large datasets and distributed training workflows* Familiarity with feature stores, model registries, and experiment tracking tools* Contributions to internal or open‑source ML libraries/platforms* Ability to mentor junior engineers and influence engineering best practices**WHAT WE OFFER:*** Real opportunities to grow your talent in a fast-moving, global organization* A fun, open, and inclusive workplace that encourages innovative thinking* Possibility to develop your language skills in our multilingual offices* Opportunities for professional growth with access to training platforms like* Comprehensive benefits: Private medical insurance, additional Life insurance, Employee Assistance Program (EAP), Employee Stock Purchase Plan (ESPP) after one year of employment
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