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Machine Learning Engineer Opt Jobs in Louisiana (NOW HIRING)

Bausch + Lomb

AI Agent ML Engineer

Baton Rouge, LA

$165K - $190K/yr

The AI Agent & ML Engineer will design, build, and optimize intelligent agents powered by advanced machine learning models, enabling process automation and decision support across Bausch + Lombs ...

Autodesk

$86K - $118K/yr

Autodesk is seeking a Senior ML Engineer, ML Systems and Infrastructure to design and scale the systems that enable machine learning across research and product development. You will help build the ...

GE Aerospace

Software Engineer AI/ML

New Orleans, LA

$105K - $126K/yr

We're looking for an AI Engineer to help transform GE Aerospace operational data into production-grade machine learning pipelines, models, and LLM-powered applications. This is a multi-faceted ...

Deloitte

Google AI Lead Architect

New Orleans, LA · On-site

$53 - $72.75/hr

Preferred : • Google Professional Machine Learning Engineer certification or the equivalent ML certification. • Master's degree in technology-related discipline. • 2+ years' leading high ...

Pwc

AI & GenAI Data Scientist - Manager

New Orleans, LA · On-site

$99K - $232K/yr

In this role at PwC, you will apply data, algorithms, and software engineering to build and deploy software and platform systems that create Artificial Intelligence and Machine Learning-based ...

CGI Inc.

Senior AWS Cloud Engineer

Lafayette, LA · On-site

$53.25 - $71.25/hr

Senior AWS Cloud Engineer Category: Infrastructure/Cloud Main location: United States, Louisiana ... AWS Machine Learning * AWS Machine Learning * Cloud architecture * Docker * GitLab What you can ...

Deloitte

Software Product Architect

New Orleans, LA · On-site

Experience with machine learning operations, AgentOps, DevSecOps, site reliability engineering, Azure DevOps, GitHub, and SonarQube * Experience with continuous integration/continuous deployment and ...

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Machine Learning Engineer Opt information

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What is the difference between Machine Learning Engineer Opt vs Data Scientist?

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

Is a machine learning engineer still in demand?

Yes, machine learning engineers are in high demand due to the growing adoption of AI and data-driven solutions across industries. They are sought after for their skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, and cloud platforms, making this a strong career choice for those with relevant expertise.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances because they develop and refine AI models, requiring specialized skills in programming, data analysis, and domain knowledge. Jobs that involve complex problem-solving, creativity, and emotional intelligence, such as healthcare professionals, educators, and skilled tradespeople, are also expected to persist despite AI automation. Continuous learning and adapting to new tools and technologies will be essential for job security across many fields.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What is a $900,000 AI job?

A $900,000 AI-related job typically refers to high-level roles such as senior machine learning engineers, AI research directors, or chief AI officers, often in large tech companies or specialized firms. These positions usually require advanced skills in machine learning, deep learning, and data science, along with extensive experience and leadership responsibilities.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or tech, can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.
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Machine Learning Engineer Opt jobs near you
Embedded Firmware Engineer

Embedded Firmware Engineer

TRUCE Software

Baton Rouge, LA

$80K - $110K/yr

Other

Posted 28 days ago

Job description

Description

About TRUCE Software


TRUCE Software is the leading provider of workplace and fleet safety solutions. Our software automatically manages mobile device usage, helping organizations reduce distractions, improve compliance, and create safer workplaces.


About the Role


We are expanding our Baton Rouge engineering team to support development of next-generation TRUCE products, including a custom dash camera platform. This role is ideal for an embedded engineer who enjoys working close to hardware and defining systems from the ground up. Because this position involves hands-on board bring-up, hardware debugging, and lab-based validation, regular in-office collaboration is expected. Remote flexibility is available when lab presence is not required.


You will work across embedded firmware, wireless communication (Wi-Fi and Bluetooth), camera systems, and on-device machine learning while owning firmware quality, validation strategy, and long-term reliability.


What You'll Work On

  • Design and implement embedded firmware for custom dash camera platforms
  • Develop multimedia pipelines including RTSP streaming and SD card storage
  • Integrate and configure camera sensors for capture and tuning
  • Develop and maintain wireless communication (Wi-Fi, Wi-Fi Aware/NAN, Bluetooth)
  • Enable execution of pretrained ML inference models on embedded hardware
  • Optimize firmware for performance, memory, power, and long-duration stability
  • Bring up and debug new hardware in collaboration with the electrical engineering team
  • Contribute to firmware architecture and long-term platform strategy

Validation & Testing Ownership

  • Develop structured test plans and detailed test cases
  • Execute system-level validation across video, storage, wireless, and ML subsystems
  • Build automated regression and test tooling (Python or similar)
  • Develop hardware-in-the-loop (HIL) or bench-level test environments
  • Support manufacturing test and production firmware validation
  • Investigate field failures and implement corrective actions

Why This Role

  • Own firmware for a new hardware platform from early development through production
  • Direct access to hardware labs for rapid iteration
  • Work on a product combining embedded systems, video, wireless, and ML
  • Influence architecture and validation strategy early
  • Small, high-impact engineering team
  • Real-world safety product with measurable impact

Requirements

Required Qualifications

  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or related field
  • Professional experience developing embedded firmware in C/C++
  • Experience with real-time or resource-constrained systems
  • Experience interfacing with hardware peripherals (SPI, I2C, UART, etc.)
  • Strong debugging skills at the firmware / hardware boundary
  • Experience developing structured test plans and system-level validation
  • Ability to work onsite in Baton Rouge on a regular basis


Preferred Experience

  • Wi-Fi and/or Bluetooth experience in embedded systems
  • RTSP, video streaming, or multimedia pipeline experience
  • Camera module or image sensor integration
  • SD card interfaces and embedded file systems
  • Machine-learning inference deployment on embedded devices
  • RTOS or bare-metal systems
  • Python for tooling, automation, or testing
  • Experience supporting product validation or manufacturing test

*Must be available for in-person interviews. 

Apply