Machine Learning Engineer Mid-Level

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 cuttingedge 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 crossfunctional 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 welldocumented 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 treebased

solutions etc.).

Create and analyze datasets conduct experiments and finetune 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 handson 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 opensourced libraries.

Knowledge of/experience in LLM (Large Language Models) finetuning and training techniques.

Strong analytical and problemsolving 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
  

• Performancebased bonus system
  

• Professional development budget
  

Qualifications: - 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!