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Multimodal Learning Jobs in Louisiana (NOW HIRING)

Spotify

$184K - $262K/yr

Working at the intersection of machine learning, platform engineering, and regulatory compliance ... Develop and maintain ML models for content moderation, including multimodal and LLM-based systems

Forward Air

Freight Handler AM

Kenner, LA

$12.75 - $16.25/hr

... multimodal transportation terminal, intermodal yard, warehouse, or dock environment, directly ... Perform tasks under appropriate supervision while learning equipment operation, safety protocols ...

Forward Air

Forklift Operator

Kenner, LA · On-site

$14.25 - $16.75/hr

... multimodal transportation terminal, intermodal yard, warehouse, or dock environment, directly ... Perform tasks under appropriate supervision while learning equipment operation, safety protocols ...

Forward Air Corporation

Freight Handler AM

Kenner, LA · On-site

$12.75 - $16.25/hr

... multimodal transportation terminal, intermodal yard, warehouse, or dock environment, directly ... Perform tasks under appropriate supervision while learning equipment operation, safety protocols ...

The Mutual Group

Lead AI Engineer - AWS Platform

Iowa, LA · On-site +1

$130K - $190K/yr

Build machine learning models that automate their training, validation, monitoring, and retraining ... Build ingestion for multimodal content and transformation pipelines for structured and unstructured ...

All JobsMultimodal Learning JobsMultimodal Learning Jobs in Louisiana

Multimodal Learning information

What is multimodal learning?

Multimodal learning is an area of machine learning that involves integrating and processing information from multiple types of data, such as text, images, audio, and video. The goal is to create models that can understand and make predictions based on more than one data modality, similar to how humans use various senses. This approach is used in applications like speech recognition with visual cues, image captioning, and video analysis. By combining different data types, multimodal learning systems can achieve better accuracy and more robust understanding.

What is the difference between Multimodal Learning vs Data Scientist?

AspectMultimodal LearningData Scientist
Required CredentialsAdvanced degrees in AI, Machine Learning, or Computer ScienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, AI development teams, academiaBusiness, tech companies, analytics teams
Industry UsageAI research, multimedia applications, roboticsData analysis, predictive modeling, business insights

Multimodal Learning focuses on developing AI models that process and integrate multiple data types like images, text, and audio. Data Scientists analyze data to extract insights, build models, and support decision-making. While both roles involve data and algorithms, Multimodal Learning is specialized in AI model development for complex data integration, whereas Data Scientists work broadly across data analysis and interpretation.

What are the key skills and qualifications needed to thrive in multimodal learning, and why are they important?

To excel as a Multimodal Learning Specialist, you need a solid background in machine learning, data science, and computer vision, often supported by an advanced degree in a related field. Familiarity with deep learning frameworks like TensorFlow or PyTorch, experience integrating data from diverse sources (e.g., text, audio, images), and knowledge of relevant algorithms are crucial. Strong problem-solving abilities, creativity, and effective collaboration are standout soft skills for this role. These competencies are vital for developing innovative models that can process and interpret complex, multi-source data to drive impactful AI solutions.

What are some common challenges faced by professionals working in multimodal learning roles, and how can they be addressed?

Professionals in multimodal learning frequently encounter challenges related to integrating and aligning data from multiple sources, such as text, images, audio, or video. Ensuring data quality and consistency across modalities can be complex, and developing models that effectively combine heterogeneous information often requires advanced technical skills and innovative thinking. Collaboration with domain experts and other data scientists is key to overcoming these obstacles, as is staying up to date with the latest research and tools in machine learning. Regular team meetings and cross-disciplinary workshops can help foster a collaborative environment and promote knowledge sharing.
What are popular job titles related to Multimodal Learning jobs in Louisiana? For Multimodal Learning jobs in Louisiana, the most frequently searched job titles are:
What job categories do people searching Multimodal Learning jobs in Louisiana look for? The top searched job categories for Multimodal Learning jobs in Louisiana are:
What cities in Louisiana are hiring for Multimodal Learning jobs? Cities in Louisiana with the most Multimodal Learning job openings:
Multimodal Learning jobs near you
Infographic showing various Multimodal Learning job openings in Louisiana as of July 2026, with employment types broken down into 1% As Needed, 77% Full Time, 20% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Senior Machine Learning Engineer - Policy & Safety

Spotify

On-site

$184K - $262K/yr

Other

Medical, Retirement, PTO

Re-posted 2 days ago

Job description

We design Spotify's consumer experience-end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints-from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.


The Policy & Safety team sits within Content Platform in the Experience Mission, building the systems that keep Spotify safe, compliant, and trusted by millions of users and creators. This team owns Spotify's content moderation infrastructure - from detection models to policy enforcement systems and compliance data pipelines.

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 path for every new content type and social feature - including messaging, comments, and collaborative experiences - ensuring safety is built in from day one. With a strong focus on "safety by default," the team is investing in large-scale rearchitecture and ML-driven systems to proactively protect users and empower safer interactions across the platform.

What You'll Do

  • Design, build, and ship production-grade machine learning systems that power content safety and policy enforcement at Spotify scale

  • Own and lead key technical initiatives across detection, classification, and policy evaluation systems

  • Develop and maintain ML models for content moderation, including multimodal and LLM-based systems

  • Build robust evaluation frameworks, including standardized datasets, offline and online metrics, and continuous improvement loops

  • Drive experimentation to improve model performance, reliability, and fairness in safety-critical systems

  • Collaborate closely with cross-functional partners in Trust & Safety, Legal, and Public Affairs to align on policy and enforcement needs

  • Provide technical leadership within the team, mentoring engineers and contributing to ML strategy and prioritization

  • Represent technical decisions and trade-offs in stakeholder discussions and influence product direction

Who You Are

  • You have solid experience building and deploying machine learning systems in production environments at scale

  • You are experienced with training, evaluating, and maintaining ML models using modern frameworks such as PyTorch

  • You have a deep understanding of machine learning evaluation, including dataset design, metrics, and continuous improvement systems

  • You know how to design systems that balance performance, reliability, and real-world impact in high-stakes domains

  • You care about building safe, responsible, and user-centric ML systems

  • You are comfortable working across disciplines, partnering with legal, policy, and product stakeholders

  • You have experience leading technical projects and influencing direction within a team or product area

  • You have experience with distributed systems or backend technologies (e.g., Scala)

Where You'll Be

  • This role is based in New York

  • We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.

The United States base range for this position is $184,050 - $262,928 USD, plus equity. The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave. These ranges may be modified in the future.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice
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