United States
1 month ago

Job Overview

Job Type
Full Time
Pay
Not disclosed

Job description

Location:
United States
Work arrangement:
On-site

Role Summary

This is a remote position.

We are seeking a skilled and motivated Machine Learning Engineer to join our team. As a Machine

Learning Engineer at Ventera, you will have the opportunity to work on cutting-edge projects that leverage the AWS Machine Learning ecosystem (SageMaker, EC2/ECS, S3 buckets, etc.). Your primary responsibilities will involve developing, deploying, and maintaining dozens of machine learning models in production using AWS services, as well as optimizing data pipelines for maximum efficiency. The current model development focus is on Anomaly Detection Timeseries prediction, with more added projects in the future.

Responsibilities

  • Collaborate with cross-functional teams to understand business needs and develop machine learning

solutions.

  • Utilize AWS SageMaker, EC2/ECS, AWS SDK, S3 buckets and the rest of the AWS ML ecosystem to build,

train and deploy machine learning models at scale.

  • Develop and maintain clean, efficient, and well-documented Python code following best coding

practices.

  • Knowledge of deep learning frameworks such as PyTorch/Tensorflow, and other ML packaged libraries

to design and implement machine learning algorithms (i.e. DARTS for timeseries, PyCaret for tree-based solutions, etc.).

  • Create and analyze datasets, conduct experiments, and fine-tune models to achieve optimal

performance.

  • Use SageMaker Notebooks and other relevant tools for data exploration, visualization, and model

evaluation.

  • Stay up to date with the latest advancements in machine learning and AWS services to drive innovation

within the team.

Requirements

  • Bachelors or Masters degree in Computer Science, Machine Learning, or a related field.
  • 2 to 3 years of hands-on experience as a Machine Learning Engineer.
  • Proficiency in Python and strong coding skills with a focus on clean and efficient code.
  • Experience with AWS services, particularly SageMaker, EC2/ECS, AWS SDK, and S3 buckets.
  • Familiarity with AIML frameworks such as PyTorch/Tensorflow/other open-sourced libraries.
  • Knowledge of/experience in LLM (Large Language Models) fine-tuning and training techniques.
  • Strong analytical and problem-solving skills.
  • Excellent communication and teamwork abilities.
  • Great all around get it done attitude. Although we work remotely, the team here has a great culture,

and we are looking to maintain that great team!

Additional Nice to Have Qualifications

  • Previous experience with Docker and containerization within AWS.
  • Knowledge of serverless computing using AWS Lambda.
  • Understanding of MLOps and DevOps practices, particularly model deployment.
  • Experience with version control systems like Git.
  • Experience with multivariate time series forecasting.
  • Experience using publisher/subscriber for messaging queues.
  • Experience developing front end applications for data science POCs.
  • Experience in an Agile coding environment is a bonus (though not required, that can be picked up

quickly).

Benefits

  • Competitive salary
  • Fully paid CareFirst BCBS Medical, Dental, and Vision coverage for you and your family
  • Amazing team and great management that takes good care of their employees
  • Generous paid time off and 11 paid holidays
  • 401(k) retirement plan with employer matching
  • Performance-based bonus system
  • Professional development budget
Role:
Machine Learning Engineer (Mid-Level)
Job Type:
Full Time

Company profile

Lion Federal

lionfederal.com

Lion Federal is an information technology consulting firm working in generative AI, machine learning and data science. It provides custom software development, data science, cloud support services and facilities design engineering to the U.S. government and commercial clients, using an Agile methodology. The SBA certifies Lion Federal as an 8(a) minority-owned Small Disadvantaged Business. The firm applies generative AI to help its clients increase efficiency.

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