Machine Learning Engineer, Consultant

Jobot Consulting; Phoenix (AZ); Remote; USD 125,000 - 150,000; Full time

Job summary

Join a leading healthcare organization as a Machine Learning Engineer, focusing on Electronic Health Records and scalable ML infrastructures. This role offers the chance to lead engineering efforts, collaborate with diverse teams, and develop AI pipelines that meet technical and business requirements. Work remotely with flexible hours while contributing to innovative projects that enhance healthcare delivery. If you have a passion for machine learning and a background in healthcare, this is an exciting opportunity to make a real impact in the industry.

Benefits

W2 or C2C Options

Flexible Remote Work

PST Hours

12+ Month Contract

Qualifications

• 3+ years of experience as a Machine Learning Engineer with a focus on production deployment.
• Proficiency in developing scalable ML infrastructures using cloud platforms.

Responsibilities

• Lead engineering efforts to create and implement ML workflows and methods.
• Collaborate with teams to design robust deployment pipelines for ML models.

Skills

Machine Learning

Production Deployment

AI Pipeline Development

Collaboration

Monitoring and Logging

Security and Compliance

Education

Bachelor’s Degree in Computer Science

Master’s Degree

Certification(s) in Machine Learning

Tools

Docker

Kubernetes

AWS

GCP

Azure

CI/CD Pipelines

Job description

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This range is provided by Jobot Consulting. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$75.00/hr - $90.00/hr

Job details:

Looking for Healthcare focused within Electronic Health Records. Proficiency in Containerization Tech exp with Docker, Kubernetes, or similar. REMOTE PST hours.

A Bit About Us: A leading healthcare organization on the west coast that focuses on EHR environments. Apply today to learn more about this Healthcare focused contract role!

• Please note you must have EHR and Healthcare setting experience to be considered.

Why join us?

• 12+ Month Contract
• REMOTE
• PST Hours
• W2 or C2C Options

Job Details

Desired Experience for a Machine Learning Engineer:

• 3 or more years relevant Machine Learning Engineer Experience
• Production Deployment and Model Engineering Proven experience in deploying and maintaining production-grade machine learning models, with real-time inference, scalability, and reliability.
• Scalable ML Infrastructures Proficiency in developing end-to-end scalable ML infrastructures using on-premise cloud platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Azure.
• Engineering Leadership Ability to lead engineering efforts in creating and implementing methods and workflows for ML/GenAI model engineering, LLM advancements, and optimizing deployment frameworks while aligning with business strategic directions.
• AI Pipeline Development Experience in developing AI pipelines for various data processing needs, including data ingestion, preprocessing, and search and retrieval, ensuring solutions meet all technical and business requirements.
• Collaboration Demonstrated ability to collaborate with data scientists, data engineers, analytics teams, and DevOps teams to design and implement robust deployment pipelines for continuous improvement of machine learning models.
• Continuous Integration/Continuous Deployment (CI/CD) Pipelines Expertise in implementing and optimizing CI/CD pipelines for machine learning models, automating testing and deployment processes.
• Monitoring and Logging Competence in setting up monitoring and logging solutions to track model performance, system health, and anomalies, allowing for timely intervention and proactive maintenance.
• Version Control Experience implementing version control systems for machine learning models and associated code to track changes and facilitate collaboration.
• Security and Compliance Knowledge of ensuring machine learning systems meet security and compliance standards, including data protection and privacy regulations.
• Documentation Skill in maintaining clear and comprehensive documentation of ML Ops processes and configurations.

Preferred Qualifications

• Proficiency in Containerization Technologies Experience with Docker, Kubernetes, or similar tools.
• Healthcare Expertise Understanding of healthcare regulations and standards, and familiarity with Electronic Health Records (EHR) systems, including integrating machine learning models with these systems.
• Master’s Degree a plus
• Bachelor’s Degree in computer science, artificial intelligence, informatics or closely related field
• Certification(s) in Machine Learning a plus

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Seniority level

Not Applicable

Employment type

Contract

Job function

Engineering and Information Technology

Industries

IT Services and IT Consulting and Software Development

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