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Freelance Machine Learning Engineer Jobs in Louisiana

AI Engineer

New Orleans, LA · On-site

$50K - $112K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials - Building ...

AI Solutions Engineering Delivery Lead

New Orleans, LA · On-site

$98K - $129K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Delegating tasks to Junior Data Engineers to realize the successful completion of projects ... Knowledge of a variety of machine learning techniques (clustering, decision tree learning ...

New

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Lead Forward Deployed Engineer - AWS

New Orleans, LA · On-site

$98K - $129K/yr

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

NGA AI Engineer Manager

New Orleans, LA · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Engineers in this role move between software development, modeling and simulation, field ... Machine learning applied to physical systems - learned dynamics or sensor models, data-driven ...

Showing results 41-60

Freelance Machine Learning Engineer information

See Louisiana salary details

$12

$40

$113

How much do freelance machine learning engineer jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for freelance machine learning engineer in Louisiana is $40.80, according to ZipRecruiter salary data. Most workers in this role earn between $20.77 and $52.84 per hour, depending on experience, location, and employer.

What does a freelance machine learning engineer do?

A Freelance Machine Learning Engineer designs, develops, and implements machine learning models and algorithms for clients on a project basis. They work independently to analyze data, build predictive models, and help businesses solve complex problems using AI and machine learning techniques. Their responsibilities may also include data preprocessing, model evaluation, and deploying solutions into production environments. Freelance Machine Learning Engineers often collaborate remotely with teams and must manage their own schedules and client relationships.

What are the key skills and qualifications needed to thrive as a freelance machine learning engineer?

To thrive as a Freelance Machine Learning Engineer, you need expertise in programming (especially Python), a solid grasp of machine learning algorithms, and a relevant academic background such as a degree in computer science, mathematics, or engineering. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (AWS, GCP, Azure), and experience with version control systems are typically required. Strong problem-solving, self-management, and client communication skills help set successful freelancers apart. These competencies are crucial for delivering effective solutions, managing projects independently, and building client trust in a competitive market.

How do freelance machine learning engineers typically manage client expectations and project scopes?

Freelance machine learning engineers often work with clients who may not have a deep technical understanding of AI or data science. A common challenge is clearly defining the project scope and deliverables at the outset, ensuring both parties understand what is feasible given the data, time, and budget constraints. Successful freelancers use regular progress updates, milestone-based deliverables, and transparent communication to manage expectations and avoid scope creep. Building trust through clear documentation and setting realistic timelines also helps foster long-term client relationships.

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

AspectFreelance Machine Learning EngineerData Scientist
CredentialsTypically requires a degree in computer science, data science, or related fields; certifications in machine learning or AI are a plusUsually holds a degree in statistics, data science, or related areas; certifications in data analysis or visualization are common
Work EnvironmentIndependent, project-based work often remotely for various clientsOften employed full-time in organizations or consulting roles, sometimes freelance
Industry UsageUsed across tech, finance, healthcare, and startups for deploying ML modelsApplied in research, analytics, and strategic decision-making across industries

Freelance Machine Learning Engineers focus on developing and deploying ML models independently for diverse clients, while Data Scientists analyze data to extract insights, often working within organizations. Both roles require strong technical skills, but their work scope and environment differ significantly.

What are the most commonly searched types of Machine Learning Engineer jobs in Louisiana?

The most popular types of Machine Learning Engineer jobs in Louisiana are:

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

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

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

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

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

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

Infographic showing various Freelance Machine Learning Engineer job openings in Louisiana as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $84,854 per year, or $40.8 per hour.

Manager of Machine Learning - AI Modeling and Operation

Workiva Inc.

Iowa, LA • On-site

$163 - $290/hr

Other

Retirement

Posted 2 days ago

New


Workiva rating

9.9

Company rating: 9.9 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

1st of 245 rated software companies


Job description

Join our team at Workiva as an Manager of Machine Learning - AI Modeling and Operation! As a pivotal member of our AI/ML team, you’ll own the infrastructure that makes every AI feature at Workiva reliable, observable, and deployable. You will lead the team responsible for ML infrastructure, model operations, and AI quality at Workiva. Your team owns the systems that make AI reliable in production from model lifecycle management to evaluation frameworks, observability, and model routing across frontier providers. You'll build the operational backbone that every AI feature at Workiva depends on. Join us if you want to own the infrastructure layer that makes enterprise AI work at scale, not just build demos. Discover more about Workiva's Generative AI.

What You’ll Do
  • Operational Excellence
  • Own the ML model lifecycle: training pipelines, model registry, deployment, monitoring, and guardrails
  • Build and maintain CI/CD for ML - automated testing, evaluation, and promotion of models across environments
  • Drive observability across AI services: latency tracking, drift detection, cost monitoring, alerting
  • Establish SLOs/SLIs for AI services and lead incident response for ML-related production issues and maintain high service availability
  • Reduce complexity through simplification, automation, and thoughtful system design
  • Leadership & Team Management
  • Lead and grow an existing strong team of machine learning engineers
  • Provide hands-on coaching, performance feedback, and growth opportunities for engineers at varying experience levels
  • Foster a collaborative, inclusive, and high-ownership team culture grounded in trust, accountability, and continuous improvement
  • Cross Functional Collaboration
  • Partner with Intelligence pillar engineering squads (AGFW, AIEI, AIQG, Applied AI, Search) and Product teams to ensure AI services are production-ready, operationally sound, and observable
  • Communicate complex technical issues to both technical and non-technical audiences effectively
  • Technical Strategy & Execution
  • Manage integrations with frontier model providers (AWS Bedrock, Azure OpenAI, Google) including model routing, load balancing, and fallback strategies
  • Drive AI analytics dashboards that give leadership and product visibility into platform health and usage
  • Drive improvements in latency, service availability, developer experience, and integration usability across internal and external interfaces
  • Guide architectural decisions to ensure platform scalability, reliability, and alignment with Workiva’s long-term technical vision
What You’ll NeedMinimum Qualifications
  • Bachelor's degree in Computer Science, Engineering, Data Science or equivalent combination of education and experience
  • 7+ years of total experience in software engineering and/or Machine Learning, with at least 2 years of dedicated experience as an Engineering Manager
  • Experience with ML pipeline orchestration tools (ClearML, Kubeflow, Airflow, or similar)
  • Hands‑on background with Kubernetes, microservices, container orchestration, and infrastructure‑as‑code
  • Track record of improving reliability/availability metrics for production ML systems
  • Proven ability to manage senior individual contributors, resolve technical conflicts, and build a culture of psychological safety and high performance
  • Solid leadership skills in an Agile/Sprint working environment
  • Experience operating production ML systems in cloud environments (AWS, Azure, or GCP)
Preferred Qualifications
  • Master’s degree in Computer Science, Engineering, Data Science or equivalent combination of education and experience
  • Experience with core concepts of Generative AI such as RAG, Agentic frameworks, etc
  • Experience building model evaluation or quality measurement systems
  • Familiarity with cost optimization for GPU/model serving workloads
  • Familiarity with observability tooling (Datadog, Prometheus, Grafana)
Working Conditions
  • Willingness to travel up to 15% for team and corporate meetings, fostering relationships and representing company interests
  • Reliable internet access for remote working opportunities
How You’ll Be Rewarded
  • Salary range in the US: $163,000.00 - $290,000.00
  • A discretionary bonus typically paid annually
  • Restricted Stock Units granted at time of hire
  • 401(k) match and comprehensive employee benefits package

The salary range represents the low and high end of the salary range for this job in the US. Minimums and maximums may vary based on location. The actual salary offer will carefully consider a wide range of factors, including your skills, qualifications, experience and other relevant factors.

Why Join Workiva

Workiva is the platform designed to bring confidence, control, and a competitive edge to the world’s most complex organizations. Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation—ensuring data is trusted, traceable, and ready to act on. With an unbroken path from source to output, leaders gain confidence in their numbers, visibility into current and emerging risks, and the ability to move with speed and precision in a constantly changing world. At Workiva, you’ll bring technology to market that executives, boards, and regulators depend on. The work you do here helps organizations navigate uncertainty, maintain trust, and make decisions that stand up to scrutiny. If you’re energized by meaningful challenges, inspired by collaborative teams, and motivated to help organizations turn uncertainty into advantage, we’d love to meet you.

Employment decisions are made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other protected characteristic. Workiva is committed to working with and providing reasonable accommodations to applicants with disabilities. Workiva employees are required to undergo comprehensive security and privacy training tailored to their roles, ensuring adherence to company policies and regulatory standards. Workiva supports employees in working where they work best - either from an office or remotely from any location within their country of employment.

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