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Sr. ML Ops Engineer

Company Description:

Infostretch is a pure-play digital engineering services firm focused on helping companies accelerate their digital initiatives from strategy and planning through execution. We leverage deep technical expertise, Agile methodologies and data-driven intelligence to modernize systems of engagement and simplify human/tech interaction. We deliver custom solutions that meet customers’ technology needs wherever they are in their digital lifecycle. Backed by Goldman Sachs and Everstone Capital, Infostretch works with both large enterprises and emerging innovators -- putting digital to work to enable new products and business models, engage with customers in new ways, and create sustainable competitive differentiation.

Job Description & Qualifications

Sr. ML ops Engineer - San Antonio, TX.  

Job Duties:

  • Work with cross functional teams for effective integration and support of ML models in product lines
  • Proficient in programing techniques and languages and development capabilities such as Python, Spark, Scala, etc.
  • Collaborate with ML, Data, Solution, and Software architects in enforcing and implementing solution patterns for machine learning design lifecycle (MLDLC) and machine learning operations (MLOps) that enable new ML capabilities, advance the ML program and drive adoption across the enterprise
  • Implement design strategies to handle risks and monitoring of model lifecycle processes such as: Experiment metadata documentation, artifact versioning, and reproducibility, Model fairness and explain ability, Model robustness and vulnerabilities
  • Work closely with Data science and other Advanced Analytical teams to decompose Models for scalability and maintainability during model deployment

 

Job Specification:

Knowledge

  • Advanced knowledge and understanding of a variety of architectural patterns, required solution implementation, operational considerations, and program management functions for ML initiatives
  • Hands-on experience developing and deploying Data Science and ML capabilities in production at scale
  • Including experience in implementing of top ML frameworks such as TensorFlow, Keras, PyTorch, SciKit, etc. with structured and unstructured data
  • Advanced Model Lifecycle understanding and design experiences for processes needed to support model monitoring areas such as:
  • Experiment metadata documentation, artifact versioning, and reproducibility
  • Model fairness and explainability
  • Model robustness and vulnerabilities
  • Propose and implement common ML model governance processes, ethical considerations and traditional data governance patterns and practices

 

Skills:

  • Must have excellent oral and written communication skills, and the ability to prioritize and handle multiple tasks
  • Ability to distinguish and align ML initiatives to business transformation goals and milestones
  • Ability to understand requirements and needs and effectively evaluate appropriate ML technology needed to meet needs Ability to Implement integrated monitoring of model performance for reliability and maintenance

 

Requirements:

  • Master’s degree in Data Science, Mathematics, Statistics, or related quantitative field
  • Minimum 5 years’ experience developing, deploying, and monitoring ML models in production environments
  • Expert Python or R using analytics and ML libraries such as Scikit Learn, Seaborn, MatplOTLIB, Pandas, NumPy, XGBoost, etc.

 

Disclaimer:
If you feel that this is a good match for your skillsets, please submit a current word version of your resume along with a cover letter describing your skills, experience and salary expectations. We are an Equal Opportunity Employer (EOE). You can read our job applicant privacy policy here.

Apply Online Print

Job Code: GA-ML-2022042101

Category: Engineering

Job Type: Contractor

Location: Dallas, TX, USA

Open Positions: 2

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