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Machine Learning Engineer (Mid-Level)

Role overview

Qualifications

  • Bachelor's or Master's 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 with clean, efficient code.
  • Experience with AWS services, particularly SageMaker, EC2/ECS, AWS SDK, and S3.

Responsibilities

  • Collaborate with cross-functional teams to understand business needs and develop machine learning solutions.
  • Build, train, and deploy machine learning models at scale using AWS SageMaker, EC2/ECS, AWS SDK, and S3.
  • Develop and maintain clean, efficient, and well-documented Python code following best practices.
  • Design and implement ML algorithms using frameworks like PyTorch/TensorFlow and other libraries; create and analyze datasets, run experiments, and fine-tune models for optimal performance.

About the company

Lion Federal logo

Lion Federal

IT Services & IT Consulting

Lion Federal, a pioneer and market leader in Generative Artificial Intelligence (GenAI), Machine Learning (ML), and Data Science, delivers cutting-edge innovative solutions with custom software development, data science, cloud support services, and facilities design engineering. Harnessing the power of Generative AI, Lion Federal provides revolutionary and transformational solutions to significantly increase efficiency to the U.S. government and commercial clients. Lion Federal is certified by the SBA as an 8(a) minority-owned Small Disadvantaged Business (SDB) with preferred status for small business contracts to the US government.

Company details

Company typeStartup
IndustryIT Services & IT Consulting
Company size11 - 50

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Job description

This is a remote position.

Job Description:
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.

Key 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

Qualifications:
- 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



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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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