Staff Machine Learning Ops Engineer - San Antonio, Dallas, Austin, Texas

Key Skills

Aartificial intelligence, Data Engineering, Data pipelines, Data science techniques, DataDog, Dataform, Docker, Google BigQuery, Google Cloud Platform (GCP), Kubernetes-K8s, Linear regression, Machine learning techniques, MLOps tools, PySpark, Python Programming, Scala Programming, TensorFlow

Job Description

Our Partners thrive The H-E-B Way. In the Staff Software Engineer job, that means you have a...

HEART FOR PEOPLE... you can serve as technical authority and coordinate work for a group of engineers

HEAD FOR BUSINESS... you make sound, mature technical judgments that result in significant impact

PASSION FOR RESULTS... you can deliver sweeping technical initiatives with minimal guidance

H-E-B is looking for highly motivated Staff Engineer. Bring your passion and dedication, and there's no telling what you could accomplish. If working in a fast-paced environment that challenges your technical abilities on a day-to-day basis is exciting to you, you have found your new home.

• Assembling large, complex sets of data that meet non-functional and functional business

  requirements.

• Has experience leading a team through End to End development – Data Extraction, Data

  Engineering, Feature Engineering, Testing and training, Model development and deployment.

• Has vast experience and hands-on in building Enterprise level applications.
• Mentoring team of Engineers with Industry’s best practices.
• Identifying, designing, and implementing internal process improvements including redesigning

  infrastructure for greater scalability, optimizing data delivery, and automating manual

  processes.

• An expert at building high quality, scalable and resilient distributed systems.
• Building required infrastructure for optimal extraction, transformation and loading of data from

  various data sources using GCP technologies.

• Improving internal processes through machine learning (ML), including increasing velocity in
• ML model building, reducing time to production, and providing solutions for production-level
• ML challenges such as versioning, lineage, and reproducibility.
• Working with stakeholders including product teams to support their Technical Product needs

  while assisting the data- related technical issues.

• Building Analytics and solutions to enable business users in making time-sensitive and critical

  decisions.

• Has researched and implemented various models including but not limited to DNN, xgBoost,
• Biq Query Arima, Linear Regression, Decision tree
• Has increased accuracy of model and identified and fixed Data drifts and model drifts.
• Build predictive models and machine-learning algorithms using distributed computing for Data Engineering and Training.
• Expertise designing and implementing data pipelines using modern data engineering approach and tools: PySpark, Scala Scala, Dataproc, Databricks etc.
• Focus on analyzing and interpreting data to find insights, trends and patterns.
• Create analytics solutions for businesses by combining various tools, applied statistics, and machine learning
• Lead discussions and initiatives and assess the feasibility of AI/ML solutions for business processes and outcomes
• We are looking for someone with at least four 10+ years of professional experience as a ML Engineer/Data science/Data Engineer, a bachelor’s degree in CS/EE and are self-driven, highly motivated and able to learn quickly.

Technologies

• Python, Scala
• Spark, Ray
• Kubernetes, Docker, Dataform and ML pipelines
• Big Query
• Databricks, Dataproc
• Vertex AI, Bigquery ML, TensonFlow
• Datadog, Relic