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Machine Learning Engineer Jobs in Baton Rouge, LA

JM TEST SYSTEMS LLC

Senior Sales Analyst

Baton Rouge, LA · On-site

$80K - $86K/yr

Partner with Data Engineering to ensure CRM data and underlying transaction data are clean ... Experience implementing AI-driven analytics, machine learning models, or predictive analytics in a ...

Varsity Tutors

Statics and Dynamics Tutor

Baton Rouge, LA · Remote

$18 - $40/hr

... machine dynamics, and advanced engineering coursework. * Conceptual Teaching & Problem-Solving ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

Varsity Tutors

Statics Tutor

Baton Rouge, LA · Remote

$18 - $40/hr

... machine design, and construction engineering. * Curriculum Awareness & Adaptive Instruction ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

Fugro

Staff Engineer - Land

Baton Rouge, LA · On-site

The Staff Engineer performs geotechnical work around the process of acquiring, analyzing ... Our talent philosophy is seeded by our values and fueled by a passion for learning, developing ...

Fugro

Staff Engineer - Land

Baton Rouge, LA

The Staff Engineer performs geotechnical work around the process of acquiring, analyzing ... Our talent philosophy is seeded by our values and fueled by a passion for learning, developing ...

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Showing results 41-60

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Baton Rouge, LA

Machine Learning Engineer information

See Baton Rouge, LA salary details

$30.3K

$123.7K

$185.8K

How much do machine learning engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for machine learning engineer in Baton Rouge, LA is $123,663.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,500.00 and $148,900.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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 strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Baton Rouge, LA? The most popular types of Machine Learning Engineer jobs in Baton Rouge, LA are:
What are popular job titles related to Machine Learning Engineer jobs in Baton Rouge, LA? For Machine Learning Engineer jobs in Baton Rouge, LA, the most frequently searched job titles are:
What cities near Baton Rouge, LA are hiring for Machine Learning Engineer jobs? Cities near Baton Rouge, LA with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Baton Rouge, LA as of August 2026, with employment types broken down into 79% Full Time, and 21% Contract. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $123,663 per year, or $59.5 per hour.

Senior Sales Analyst

JM TEST SYSTEMS LLC

Baton Rouge, LA • On-site

$80K - $86K/yr

Full-time

Re-posted 20 days ago

Job description

We are seeking a Senior Sales Analyst to serve as a keyanalytics resource for our Sales and Marketing teams. This role will beresponsible for transforming commercial data into actionable insights thatdrive revenue growth, improve sales effectiveness, and sharpen our go-to-marketstrategy. The Senior Sales Analyst will own sales performance reporting,pipeline analytics, and marketing ROI analysis - partnering closely with ourChief Revenue Officer and Sales and Marketing leadership. This role will benefitfrom the foundation built by our broader analytics and AI organizations andwill ultimately be responsible for continuing to improve how commercialdecisions are made.
Key Responsibilities
  • Sales Performance Reporting: Own the design, development, and delivery of recurring sales reports and analytics covering revenue by service line, rep-level performance, quota attainment, pipeline health, and customer retention - ensuring Sales leadership has timely, accurate visibility into the results and opportunities.
  • Sales Growth Analysis: Identify revenue growth opportunities by analyzing trends across accounts, segments, geographies, and service lines using both internal and external data sources. Surface patterns in new logo acquisition, churn, wallet share, and cross-sell to help sales teams focus their energy where it matters most.
  • Marketing & Pipeline Analytics: Support the Marketing function with campaign performance analysis, lead source attribution, and digital channel ROI. Partner with Marketing to connect top-of-funnel activity to downstream pipeline and closed revenue, informing how and where to invest for growth.
  • Sales & Marketing Enablement Tools: Build and maintain self-service tools with the help of AI and our software engineers that put actionable data directly in the hands of our Outside Sales Team, Inside Sales, and Marketing. Reduce manual reporting burdens and create scalable tools the commercial team can rely on day-to-day.
  • CRM & Data Integrity: Partner with Data Engineering to ensure CRM data and underlying transaction data are clean, consistent, and structured to support reliable commercial reporting. Flag data quality issues and drive resolution to maintain the integrity of sales analytics.
  • Forecasting & Predictive Insights: Develop and maintain sales forecasting models and apply predictive analytics to identify at-risk accounts, high-potential prospects, and seasonal revenue patterns. Leverage AI and advanced modeling where appropriate to give the commercial team a forward-looking edge.
  • Cross-Functional Collaboration: Work closely with Sales leadership, Marketing, Sales Operations, and Finance to align on metrics definitions, reporting cadences, and analytical priorities. Translate complex findings into clear narratives and recommendations that drive action at the leadership level.
  • Tool and Technology Evaluation: Stay abreast of emerging analytics and AI tools and technologies, recommending and implementing solutions that enhance the company's analytics and commercial capabilities.

Qualifications:
  • Bachelor's degree in Data Science, Statistics, Computer Science, Business Analytics, Math, Sciences, or a related field (Master's degree preferred).
  • 2+ years of experience in analytics, commercial operations, or a related business analytics role
  • Proven track record of driving data-driven decision-making and building analytics solutions in a fast-paced environment.
  • Proven track record of developing insights that lead to action and positive results
  • Experience implementing AI-driven analytics, machine learning models, or predictive analytics in a business context.
  • Strong proficiency in Claude or other LLM development tools, SQL, R, Excel, PowerPoint.
  • Experience collaborating with Data Engineering teams to design and implement data views.
  • Experience working with CRM platforms (e.g. HubSpot, Salesforce) and familiarity with sales engagement or marketing automation tools (e.g., Apollo.io, Clay, Klaviyo).
  • Excellent communication skills, with the ability to translate complex data and AI insights into clear, actionable recommendations for non-technical stakeholders.
  • Strong project management skills, with the ability to prioritize and manage multiple initiatives simultaneously.
  • General understanding of data governance, data quality, and best practices in analytics.
  • Knowledge of data warehousing concepts and ETL processes.

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