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Machine Learning Biomedical Engineer Jobs in Louisiana

Varsity Tutors

Machine Learning Tutor

New Orleans, LA · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Baton Rouge, LA · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Spotify

$184K - $262K/yr

Working at the intersection of machine learning, platform engineering, and regulatory compliance, the team partners closely with Trust & Safety, Legal, and Public Affairs. They're on the critical ...

Collabera LLC

Support Engineer

Baton Rouge, LA · On-site

$30 - $35/hr

Job Title - Artificial Intelligence / Machine Learning Support Engineer Remote - 06 weeks, then need to relocate to Baton Rouge, LA Pay Range - $30-$35/hr. Summary * This profile outlines the desired ...

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Machine Learning Biomedical Engineer information

What does a machine learning biomedical engineer do?

A Machine Learning Biomedical Engineer applies machine learning techniques to solve problems in biology and medicine. They develop algorithms and models to analyze complex biomedical data, such as medical images, genetic information, or sensor readings. Their work supports advancements in diagnostics, treatment planning, and personalized medicine. Typically, they collaborate with clinicians, researchers, and other engineers to design systems that improve healthcare outcomes.

How does a machine learning biomedical engineer typically collaborate with clinicians and researchers in a healthcare setting?

Machine Learning Biomedical Engineers often work closely with clinicians and researchers to develop algorithms that solve real-world medical challenges. Collaboration usually involves understanding clinical needs, translating them into technical requirements, and iteratively refining models based on feedback from medical experts. Regular meetings, interdisciplinary project teams, and direct participation in data collection or validation studies are common. This collaborative environment ensures that technical solutions are both innovative and clinically relevant, making communication and adaptability essential skills.

What are the key skills and qualifications needed to thrive as a machine learning biomedical engineer, and why are they important?

To thrive as a Machine Learning Biomedical Engineer, you need a strong background in biomedical engineering, data analysis, and machine learning, typically supported by a degree in biomedical engineering, computer science, or a related field. Familiarity with programming languages like Python or R, machine learning frameworks (e.g., TensorFlow, PyTorch), and experience with medical imaging or signal processing tools are commonly required. Critical thinking, problem-solving, and the ability to communicate complex technical concepts to interdisciplinary teams are vital soft skills. These abilities are crucial for developing innovative healthcare solutions, ensuring regulatory compliance, and bridging the gap between technology and medicine.

What is the difference between Machine Learning Biomedical Engineer vs Data Scientist in Biomedical Industry?

AspectMachine Learning Biomedical EngineerData Scientist in Biomedical Industry
Required CredentialsDegree in Biomedical Engineering, Computer Science, or related fields; knowledge of machine learning and biomedical dataDegree in Data Science, Statistics, or related fields; proficiency in data analysis and machine learning
Work EnvironmentResearch labs, healthcare institutions, biotech companiesHealthcare analytics firms, research institutions, biotech companies
Employer & Industry UsageDevelops algorithms for medical devices, diagnostics, and treatment planningAnalyzes biomedical data to inform clinical decisions, research, and product development

Both roles require expertise in machine learning and biomedical data, but Machine Learning Biomedical Engineers focus on developing algorithms for medical applications, while Data Scientists analyze biomedical data to support research and clinical decisions.

What are popular job titles related to Machine Learning Biomedical Engineer jobs in Louisiana?

For Machine Learning Biomedical Engineer jobs in Louisiana, the most frequently searched job titles are:

What job categories do people searching Machine Learning Biomedical Engineer jobs in Louisiana look for?

The top searched job categories for Machine Learning Biomedical Engineer jobs in Louisiana are:

What cities in Louisiana are hiring for Machine Learning Biomedical Engineer jobs?

Cities in Louisiana with the most Machine Learning Biomedical Engineer job openings:

Machine Learning Biomedical Engineer jobs near you

Senior Machine Learning Engineer

Raceland, LA

Bollinger Shipyards
Ship and Boat Building • 1 - 5K employees

6.5

Company rating: 6.5 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

People enjoy working here

Respectful managers

Learn more about Bollinger Shipyardsexternal

$99K - $136K/yr

Full-time

Re-posted 12 days ago

Job description

Job Title: Senior Machine Learning Engineer

Location: Mulitple Locations

Position Overview:

The Senior ML Engineer is responsible for operationalizing machine learning and AI solutions into scalable, reliable, and production-ready enterprise systems. This role bridges data science, software engineering, and infrastructure disciplines to deploy, monitor, optimize, and support AI solutions that drive operational and business outcomes.

Key Responsibilities: 

•             Deploy, integrate, and maintain machine learning and AI solutions within enterprise workflows and operational systems

•             Design and develop scalable ML pipelines, feature stores, APIs, and model-serving infrastructure

•             Collaborate with Data Scientists to productionize models and improve deployment readiness

•             Monitor model performance, drift, availability, and reliability across production environments

•             Implement processes for model retraining, versioning, governance, and lifecycle management

•             Partner with Data Engineering teams to support feature engineering and data pipeline integration

•             Ensure ML solutions are secure, scalable, maintainable, and aligned with enterprise architecture standards

•             Support AI applications across forecasting, operational optimization, bidding, scheduling, maintenance, and automation use cases

•             Troubleshoot and resolve issues related to model deployment and operational performance

•             Contribute to ML engineering standards, best practices, and platform improvements

•             Document architecture, deployment processes, and operational support procedures

 

Qualifications: 

·       Bachelor’s degree in Computer Science, Software Engineering, Data Science, or related field

·       6–10 years in ML or software engineering

·       Strong Python and ML deployment experience

·       Experience with cloud ML systems

 

Skills: 

•             Experience with Azure ML, Databricks, ML Ops, or similar cloud AI platforms

•             Experience in manufacturing, industrial, operational, or engineering environments

•             Familiarity with large language models, Generative AI, and intelligent automation

•             Experience supporting enterprise AI applications integrated with ERP or operational systems

•             Knowledge of monitoring, observability, and model governance practices

•             Experience with Docker, Kubernetes, and infrastructure-as-code practices

Bollinger is an equal opportunity employer and is committed to providing employment opportunities to minorities, females, veterans and disabled individuals, and without regard to sexual orientation and gender identity. 

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