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
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Design, build, and maintain data pipelines and architectures for AI/ML
applications.
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Collaborate with data scientists / engineers / analysts to collect,
process, and prepare large datasets for analysis and modeling.
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Develop, deploy, and optimize scalable machine learning models and
algorithms.
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Implement data validation, cleansing, and transformation processes to
ensure data quality and integrity.
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Leverage cloud platforms (AWS) to enable scalable data solutions.
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Monitor and improve the performance of data workflows and ML models in
production.
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Document data engineering processes and share knowledge with team members.
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Stay current with emerging technologies and best practices in data
engineering and machine learning.
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Knowledge of data security and best practices.
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Experience working with real-time data processing.
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Strong track record of cross-functional collaboration.
Who You Are (Basic Qualifications)
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Bachelor’s or master’s degree in Computer Science, Engineering, or related
field.
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5-7+ years of total experience.
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3–5 years of experience
in data engineering, with hands-on experience in AI/ML projects.
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3–5 years of experience
in the Python programming language.
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Experience with data pipeline tools (e.g., Apache Airflow, Luigi) and data
processing frameworks (e.g., Numpy, Pandas).
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Strong knowledge of SQL and experience working with relational databases.
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Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch,
Scikit-learn).
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Experience with data visualization tools (e.g., Matplotlib, Seaborn).
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Strong analytical and problem-solving skills.
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Excellent communication and collaboration skills.
What Will Put You Ahead
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Experience in applying predictive analytics techniques to generate
actionable business insights.
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Experience building and deploying machine learning models in production
environments.
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Experience with predictive analytics and statistical modeling.
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Familiarity with containerization and orchestration (e.g., Docker,
Kubernetes).
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Experience with AWS cloud data services (eg: Step function, AWS
QuickSight, etc).
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Experience with NoSQL databases.