ML Engineer (US Remote)

# Machine Learning Engineer, Consultant

## About the Role

Jobot Consulting is seeking a Machine Learning Engineer, Consultant to support a healthcare-focused organization working extensively with Electronic Health Record (EHR) environments. This remote contract role focuses on production machine learning, scalable ML infrastructure, AI/GenAI model engineering, and MLOps.

The ideal candidate has at least 3 years of relevant machine learning engineering experience, hands-on healthcare and EHR experience, and a strong background in deploying and maintaining production-grade ML systems. Experience with containerization technologies such as Docker or Kubernetes is highly relevant to the role.

## Key Responsibilities

• * Deploy and maintain production-grade machine learning models with a focus on real-time inference, scalability, and reliability.
• * Develop end-to-end, scalable ML infrastructure across on-premises and cloud environments.
• * Work with AWS, GCP, Azure, or similar cloud platforms to support machine learning infrastructure.
• * Lead engineering efforts related to ML and GenAI model engineering, LLM advancements, and deployment framework optimization.
• * Align ML engineering methods and workflows with business and technical objectives.
• * Develop AI pipelines supporting data ingestion, preprocessing, search, and retrieval requirements.
• * Ensure AI pipelines satisfy technical and business requirements.
• * Collaborate with data scientists, data engineers, analytics teams, and DevOps teams to build robust deployment pipelines.
• * Implement and optimize CI/CD pipelines for machine learning models.
• * Automate testing and deployment processes for ML systems.
• * Establish monitoring and logging solutions to track model performance, system health, and anomalies.
• * Support proactive maintenance and timely intervention when issues are identified.
• * Implement version control for machine learning models and associated code.
• * Ensure ML systems follow applicable security, data protection, privacy, and compliance requirements.
• * Maintain clear and comprehensive documentation of MLOps processes and configurations.
• * Support integration of machine learning models with healthcare and EHR systems.

## Required Qualifications

• * 3+ years of relevant Machine Learning Engineer experience.
• * Proven experience deploying and maintaining production-grade machine learning models.
• * Experience with real-time ML inference, scalability, and system reliability.
• * Experience developing scalable, end-to-end ML infrastructure.
• * Experience with cloud platforms such as AWS, GCP, or Azure.
• * Experience developing AI pipelines for data ingestion, preprocessing, search, and retrieval.
• * Experience implementing CI/CD pipelines for machine learning systems.
• * Experience with monitoring and logging for ML models and infrastructure.
• * Experience with version control for ML models and associated code.
• * Knowledge of security, data protection, privacy, and compliance requirements for machine learning systems.
• * Strong documentation skills for MLOps processes and configurations.
• * Healthcare industry experience is required.
• * Electronic Health Record (EHR) experience is required.

## Preferred Qualifications

• * Experience with containerization technologies such as Docker or Kubernetes.
• * Experience integrating machine learning models with EHR systems.
• * Understanding of healthcare regulations and standards.
• * Experience with ML/GenAI model engineering and LLM advancements.
• * Experience optimizing ML deployment frameworks.
• * Bachelor's degree in Computer Science, Artificial Intelligence, Informatics, or a closely related field.
• * Master's degree.
• * Machine Learning certification(s).

## Skills & Competencies

• * Machine Learning Engineering
• * Production ML
• * MLOps
• * Generative AI
• * LLM Engineering
• * AI Pipeline Development
• * Model Deployment
• * Real-Time Inference
• * ML Infrastructure
• * AWS
• * GCP
• * Azure
• * CI/CD
• * Monitoring and Logging
• * Version Control
• * Docker
• * Kubernetes
• * Data Ingestion
• * Data Preprocessing
• * Search and Retrieval
• * EHR Systems
• * Healthcare Technology
• * Security and Compliance
• * Technical Documentation
• * Cross-Functional Collaboration

## Education & Experience

• * 3+ years of relevant Machine Learning Engineer experience required.
• * Healthcare and EHR experience required.
• * Bachelor's degree in Computer Science, Artificial Intelligence, Informatics, or a closely related field is preferred.
• * Master's degree is a plus.
• * Machine Learning certification(s) are a plus.

## Work Arrangement & Schedule

• * Location: Bakersfield, CA, US
• * Work Arrangement: Remote
• * Time Zone: Pacific Standard Time (PST) hours
• * Contract Duration: 12+ months
• * Employment Options: W2 or C2C
• * Employment Type: Contract
• * Industry Focus: Healthcare / Electronic Health Records

## Compensation & Benefits

• * Compensation: $75–$150 per hour
• * 12+ month contract opportunity
• * Fully remote work
• * W2 or C2C engagement options
• * PST work hours

## Compliance / Additional Information

• * Healthcare and EHR experience are required for consideration.
• * The employer is an Equal Opportunity Employer and considers qualified candidates without regard to legally protected characteristics.
• * Background checks may be conducted with candidate authorization and in accordance with applicable federal, state, and local laws.