Machine Learning Engineer, Consultant

Jobot Consulting; Bakersfield (CA); Remote; USD 103,320 - 206,640; Full time

Benefits offered by this job

12+ Month Contract

Flexible Remote Work

PST Hours

W2 or C2C Options

Job summary

An established industry player is seeking a skilled Machine Learning Engineer with a focus on healthcare and Electronic Health Records. This role involves deploying scalable ML infrastructures, leading engineering efforts, and collaborating with cross-functional teams to enhance machine learning models. The ideal candidate will have a strong background in production deployment, CI/CD pipelines, and a deep understanding of healthcare regulations. Join this innovative healthcare organization and contribute to impactful projects while enjoying the flexibility of remote work and a supportive work environment.

Qualifications

• 3+ years of experience in Machine Learning Engineering required.
• Proficiency in deploying and maintaining production-grade ML models.

Responsibilities

• Lead engineering efforts for ML model engineering and deployment.
• Collaborate with teams to design robust deployment pipelines.

Skills

Machine Learning Engineering

Production Deployment

Scalable ML Infrastructures

Collaboration

CI/CD Pipelines

Monitoring and Logging

Version Control

Security and Compliance

Documentation

Healthcare Regulations

Education

Bachelor’s Degree in Computer Science

Master’s Degree

Tools

Docker

Kubernetes

AWS

Google Cloud Platform

Azure

Job description

Job details

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

Salary: $75 - $150 per hour

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

• 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

Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Sometimes Jobot is required to perform background checks with your authorization. Jobot will consider qualified candidates with criminal histories in a manner consistent with any applicable federal, state, or local law regarding criminal backgrounds, including but not limited to the Los Angeles Fair Chance Initiative for Hiring and the San Francisco Fair Chance Ordinance.