2 дня назад
Senior Data Engineer (AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Data Engineer (AI): Building scalable data pipelines and infrastructure for machine learning workflows processing complex chemistry data, chromatograms, and environmental testing results with an accent on data modeling, MLOps, and scientific data quality. Focus on designing ETL/ELT systems, deploying retraining and monitoring pipelines, and creating APIs that connect machine learning engineers with chemistry laboratory systems.
Location: Stafford, Texas, USA; onsite full-time role
Company
Scientific provides analytical testing services for food, water, medicines, and other products, with a focus on health, safety, sustainability, and environmental protection.
What you will do
- Design, build, and maintain scalable ETL/ELT pipelines for raw chemistry data, including CSV, JSON, and proprietary instrument formats.
- Develop optimized data models and manage data warehouse or data lake infrastructure for complex time-series and chromatogram spectral data.
- Collaborate with machine learning engineers to containerize and deploy models and automate model retraining and monitoring.
- Implement data quality checks, validation, and monitoring to ensure chemical experiment data is reliable and reproducible.
- Build internal tools and APIs for machine learning data access and standardized submissions from chemistry laboratory systems.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical field, or equivalent practical experience.
- Expert-level Python proficiency, including Pandas, NumPy, and data engineering libraries.
- Hands-on experience with AWS, Azure, or GCP, preferably Azure, including compute, storage, serverless functions, ADLS, Azure VMs, or Azure Functions.
- Experience with Apache Airflow, Prefect, Dagster, SQL, relational databases such as PostgreSQL, NoSQL databases, Git, and DevOps practices.
- Experience processing large-volume scientific data, such as mass spectrometry or chromatography data, and integrating with LIMS or ELN systems; familiarity with MLOps tools such as Azure ML Studio, MLflow, Kubeflow, or SageMaker.
- Must be authorized to work in the United States without restriction or sponsorship. Professional working proficiency in English is required.
Culture & Benefits
- Comprehensive medical, dental, and vision coverage.
- Life and disability insurance.
- 401(k) plan with company match.
- Paid holidays and paid time off.
- Career development support, diversity and inclusion initiatives, and sustainability programs.
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