Machine Learning Engineer

DFW Metroplex, TX

Full Time

About this role

At evolv Consulting, we are seeking to hire an experienced Machine Learning Engineer to join our team. If you’re a passionate self-starter, evolv is a great place to get ahead.
Responsibilities for this role include:
  • Prototype, design, and implement predictive models and algorithms and lead the full life cycle including data cleansing, feature creation, and iterative model selection.
  • Write maintainable and extensible tested code that adheres to standards, produce specifications, and determine operation feasibility, and troubleshoot, debut, and upgrade existing systems.
  • Collaborate closely with applied scientists on machine learning operations tasks ranging from ML data management to training and deployment of ML models.
  • Use statistical and machine learning techniques to create scalable solutions for data/analysis, and perform R&D to drive discovery of new generation products.
  • Establish scalable, efficient, automated processes for large scale data analysis, model development, model validation and model implementation.
  • Drive adoption of best practices across organizations.
  • Deliver production-ready code.
  • Work with Product Owners to define the KPIs for machine learning projects.
  • Stay abreast of developments in research methodology and changing technologies in the marketplace and proactively identify applications of these latest developments to improve existing methods.
  • Prepare and present findings to both technical and non-technical audiences.
  • Work within the constraints of time, budget, and resources capacities to align with company vision.
  • Develop and foster collaborative relationships with product, business, and engineering teams to effectively serve needs.
  • Other duties as assigned.


  • 5+ years of production experience working in Data Science or Software Engineering.
  • 3+ years of production experience in Machine Learning, Computer Vision, Signal Processing, and/or Natural Language Processing (NLP).
  • Solid production experience using Python (including NumPy) and SQL.
  • Solid production experience using TensorFlow and/or PyTorch.
  • Production experience with Apache Spark.
  • Strong fundamentals in problem solving, algorithm design and complexity analysis.
  • Experience implementing and orchestrating Machine Learning pipelines in production environments, using tools such as Kubeflow, airflow, Pachyderm, mlflow, etc.
  • Hands-on experience with web APIs, containers, Kubernetes, CI/CD and testing.
  • Experience from working in Agile Scrum environments.
  • Experience implementing solutions in a cloud environment (AWS, Azure, or Google Cloud).
  • Experience using Infrastructure-as-code for cloud infrastructure automation.
  • Experience working with data science in automotive telematics data and video is a plus.
  • Experience in edge computing is a plus.

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