About the role

Your Job

As a Data Engineer – AI/ML , you will leverage your expertise in Python, and data engineering to design and implement robust data processing workflows, develop and deploy machine learning models, orchestrate data pipelines, and create impactful visualizations. You will collaborate closely with cross-functional teams to deliver scalable solutions that drive business value, while continuously learning and applying the latest technologies to solve complex challenges.

Our Team

Join the Software Solution Group (SSG), the central nervous system of the Copper Solutions Business Unit (CSBU), driving digital transformation in electronics interconnect manufacturing for our Datacom &Specialty Solutions (DSS) division. As the core software team, we develop advanced tools and analytics that optimize the production of high-performance cable assemblies—essential to global data networks. Collaborating closely with engineers and manufacturing experts, we turn complex production data into actionable insights, enhancing the design and manufacturing of cable assemblies that power today’s data centers, telecom networks, and storage devices.

In our dynamic team, you’ll find an environment that values creative thinking, technical curiosity, and collaboration. You’ll leverage advanced analytics, machine learning, and predictive modeling to drive process improvements and ensure top product quality. If you’re passionate about software, electronics, and shaping the future of data connectivity, you’ll thrive here.

What You Will Do

Design, build, and maintain data pipelines and architectures for AI/ML applications.
Collaborate with data scientists / engineers / analysts to collect, process, and prepare large datasets for analysis and modeling.
Develop, deploy, and optimize scalable machine learning models and algorithms.
Implement data validation, cleansing, and transformation processes to ensure data quality and integrity.
Leverage cloud platforms (AWS) to enable scalable data solutions.
Monitor and improve the performance of data workflows and ML models in production.
Document data engineering processes and share knowledge with team members.
Stay current with emerging technologies and best practices in data engineering and machine learning.
Knowledge of data security and best practices.
Experience working with real-time data processing.
Strong track record of cross-functional collaboration.

Who You Are (Basic Qualifications)

Bachelor’s or master’s degree in Computer Science, Engineering, or related field.
5-7+ years of total experience.
3–5 years of experience in data engineering, with hands-on experience in AI/ML projects.
3–5 years of experience in the Python programming language.
Experience with data pipeline tools (e.g., Apache Airflow, Luigi) and data processing frameworks (e.g., Numpy, Pandas).
Strong knowledge of SQL and experience working with relational databases.
Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
Experience with data visualization tools (e.g., Matplotlib, Seaborn).
Strong analytical and problem-solving skills.
Excellent communication and collaboration skills.

What Will Put You Ahead

Experience in applying predictive analytics techniques to generate actionable business insights.
Experience building and deploying machine learning models in production environments.
Experience with predictive analytics and statistical modeling.
Familiarity with containerization and orchestration (e.g., Docker, Kubernetes).
Experience with AWS cloud data services (eg: Step function, AWS QuickSight, etc).
Experience with NoSQL databases.