Machine Learning Engineer
Machine Learning Engineer
Posted on :
12-10-2024
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Job Description
Machine Learning Engineer
Location: Hybrid (Philadelphia PA or Washington DC)
Job Summary:
We are seeking a skilled and experienced Machine Learning (ML) Engineer to join our team in a customerfacing role. You will architect and implement innovative ML solutions working closely with data scientists and engineers to put algorithms and models into practice to solve our customers most challenging problems. You will take the lead in planning designing and running experiments while researching new algorithms to deliver impactful solutions.
Key Responsibilities:
Design build and deploy machine learning models within the proposed platform ensuring they are optimized for performance and scalability.
Collaborate with Data Scientists and Data Engineers to implement feature stores model management (MLOps) and Explainable AI (XAI) capabilities.
Monitor and optimize the performance of deployed models ensuring they meet business requirements and performance standards.
Support model management versioning and deployment workflows to streamline the operationalization of machine learning models.
Engage directly with customers to understand their business problems and help implement tailored ML solutions.
Deliver Machine Learning projects endtoend including understanding business needs planning projects aggregating & exploring data building & validating predictive models and deploying completed ML capabilities on the AWS Cloud to deliver business impact.
Utilize deep learning frameworks like PyTorch and TensorFlow to build computer vision models for versatile applications.
Work on largescale datasets creating scalable robust and accurate computer vision systems.
Collaborate with Cloud Architects to build secure robust and easytodeploy cloudnative machine learning solutions.
Work closely with customer account teams and product engineering teams to optimize model implementations and deploy cuttingedge algorithms.
Assist customers with Machine Learning Operations (MLOps) workflows such as model deployment retraining testing and performance monitoring.
Apply best practices from core Software Development activities to Machine Learning including deplorability unit testing and structured extensible software development.
Preferred Qualifications:
Proven experience in building and deploying machine learning models at scale.
Proficiency with deep learning frameworks like PyTorch and TensorFlow.
Experience with cloudnative machine learning solutions preferably on AWS.
Experience with Databricks
Experience with Agile Methodology
Strong understanding of MLOps workflows including model management.
Ability to work independently and collaboratively with crossfunctional teams.
Location: Hybrid (Philadelphia PA or Washington DC)
Job Summary:
We are seeking a skilled and experienced Machine Learning (ML) Engineer to join our team in a customerfacing role. You will architect and implement innovative ML solutions working closely with data scientists and engineers to put algorithms and models into practice to solve our customers most challenging problems. You will take the lead in planning designing and running experiments while researching new algorithms to deliver impactful solutions.
Key Responsibilities:
Design build and deploy machine learning models within the proposed platform ensuring they are optimized for performance and scalability.
Collaborate with Data Scientists and Data Engineers to implement feature stores model management (MLOps) and Explainable AI (XAI) capabilities.
Monitor and optimize the performance of deployed models ensuring they meet business requirements and performance standards.
Support model management versioning and deployment workflows to streamline the operationalization of machine learning models.
Engage directly with customers to understand their business problems and help implement tailored ML solutions.
Deliver Machine Learning projects endtoend including understanding business needs planning projects aggregating & exploring data building & validating predictive models and deploying completed ML capabilities on the AWS Cloud to deliver business impact.
Utilize deep learning frameworks like PyTorch and TensorFlow to build computer vision models for versatile applications.
Work on largescale datasets creating scalable robust and accurate computer vision systems.
Collaborate with Cloud Architects to build secure robust and easytodeploy cloudnative machine learning solutions.
Work closely with customer account teams and product engineering teams to optimize model implementations and deploy cuttingedge algorithms.
Assist customers with Machine Learning Operations (MLOps) workflows such as model deployment retraining testing and performance monitoring.
Apply best practices from core Software Development activities to Machine Learning including deplorability unit testing and structured extensible software development.
Preferred Qualifications:
Proven experience in building and deploying machine learning models at scale.
Proficiency with deep learning frameworks like PyTorch and TensorFlow.
Experience with cloudnative machine learning solutions preferably on AWS.
Experience with Databricks
Experience with Agile Methodology
Strong understanding of MLOps workflows including model management.
Ability to work independently and collaboratively with crossfunctional teams.
Employment Type
Full Time
Key Skills
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