Software Engineer Jobs at Venture Global LNG with Visa Sponsorship
Venture Global LNG hires Software Engineers to build and maintain the digital infrastructure behind large-scale LNG production and export operations. The company has an established track record of sponsoring work visas for engineering talent, making it a realistic target for international candidates in the energy sector.
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INTRODUCTION
Venture Global LNG (“Venture Global”) is a long-term, low-cost provider of American-produced liquefied natural gas. The company’s two Louisiana-based export projects service the global demand for North American natural gas and support the long-term development of clean and reliable North American energy supplies. Using reliable, proven technology in an innovative plant design configuration, Venture Global’s modular, mid-scale plant design will replace traditional designs as it allows for the same efficiency and operational reliability at significantly lower capital cost.
ROLE AND RESPONSIBILITIES
The Machine Learning Engineer will design, develop, and maintain the productionization of machine learning, deep learning, generative AI, large language models, simulation, and optimization algorithms. This includes building pipelines for training and deploying deep learning and other machine learning algorithms and enabling models to run efficiently in production. The main data engineering work will be done in Databricks and PySpark. The ideal candidate will have excellent technical proficiency, excellent communication skills, a self-driven mindset, and the willingness to continuously learn new things. This position will report to the Director of Business Intelligence and is structured within IT under the Vice President of Applications. The position will be located in Arlington, VA and will require commuting to the office 5 days a week.
- Work with business stakeholders to define project requirements.
- Orchestrate, scale, setup and improve model serving pipelines.
- Improve model accuracy through feature engineering, tuning, and observability.
- Improve model computational performance through all aspects of the pipeline, including tuning clusters/job compute, partitioning, caching, feature engineering code, tuning setup, etc.
- Integrate machine learning models into production environments, ensuring reliability and scalability.
- Evaluate pretrained models and software from vendors and support integration into production environments.
- Develop comprehensive project plans for implementing machine learning and AI projects including solution architectures, resourcing, and dependencies.
- Provide ETL requirements to data engineers to effectively curate files for data analytics.
- Work with data scientists, data engineers, and business analysts to translate business requirements into machine learning solutions.
- Build software solutions that are maintainable, scalable and provide quantifiable business value.
- Continuously focus on quality architecture, quality code, and ruthless management of technical debt.
- Continuously push the practice forward, learning and testing newer and better ways of performing work.
BASIC QUALIFICATIONS
- 5 years of machine learning engineering, software engineering, or data science experience.
- Bachelors in a quantitative field of study.
PREFERRED QUALIFICATIONS
- Masters in a quantitative field of study.
- Experience with the Azure, AWS, or other cloud ecosystems.
- Experience in building secure data processing pipelines.
- Proficient in utilizing data lakes, CI/CD pipelines, Databricks, Unity Catalog, and Git.
- Experience working with streaming.
- Expertise in building machine learning solutions using cloud data services.
- Exceptional skills in data processing languages such as SQL, Python, or Scala.
- Exceptional skills in feature engineering, model optimization, and parameter tuning.
Venture Global LNG is an Equal Opportunity Employer. We do not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law.

INTRODUCTION
Venture Global LNG (“Venture Global”) is a long-term, low-cost provider of American-produced liquefied natural gas. The company’s two Louisiana-based export projects service the global demand for North American natural gas and support the long-term development of clean and reliable North American energy supplies. Using reliable, proven technology in an innovative plant design configuration, Venture Global’s modular, mid-scale plant design will replace traditional designs as it allows for the same efficiency and operational reliability at significantly lower capital cost.
ROLE AND RESPONSIBILITIES
The Machine Learning Engineer will design, develop, and maintain the productionization of machine learning, deep learning, generative AI, large language models, simulation, and optimization algorithms. This includes building pipelines for training and deploying deep learning and other machine learning algorithms and enabling models to run efficiently in production. The main data engineering work will be done in Databricks and PySpark. The ideal candidate will have excellent technical proficiency, excellent communication skills, a self-driven mindset, and the willingness to continuously learn new things. This position will report to the Director of Business Intelligence and is structured within IT under the Vice President of Applications. The position will be located in Arlington, VA and will require commuting to the office 5 days a week.
- Work with business stakeholders to define project requirements.
- Orchestrate, scale, setup and improve model serving pipelines.
- Improve model accuracy through feature engineering, tuning, and observability.
- Improve model computational performance through all aspects of the pipeline, including tuning clusters/job compute, partitioning, caching, feature engineering code, tuning setup, etc.
- Integrate machine learning models into production environments, ensuring reliability and scalability.
- Evaluate pretrained models and software from vendors and support integration into production environments.
- Develop comprehensive project plans for implementing machine learning and AI projects including solution architectures, resourcing, and dependencies.
- Provide ETL requirements to data engineers to effectively curate files for data analytics.
- Work with data scientists, data engineers, and business analysts to translate business requirements into machine learning solutions.
- Build software solutions that are maintainable, scalable and provide quantifiable business value.
- Continuously focus on quality architecture, quality code, and ruthless management of technical debt.
- Continuously push the practice forward, learning and testing newer and better ways of performing work.
BASIC QUALIFICATIONS
- 5 years of machine learning engineering, software engineering, or data science experience.
- Bachelors in a quantitative field of study.
PREFERRED QUALIFICATIONS
- Masters in a quantitative field of study.
- Experience with the Azure, AWS, or other cloud ecosystems.
- Experience in building secure data processing pipelines.
- Proficient in utilizing data lakes, CI/CD pipelines, Databricks, Unity Catalog, and Git.
- Experience working with streaming.
- Expertise in building machine learning solutions using cloud data services.
- Exceptional skills in data processing languages such as SQL, Python, or Scala.
- Exceptional skills in feature engineering, model optimization, and parameter tuning.
Venture Global LNG is an Equal Opportunity Employer. We do not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law.
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Get Access To All JobsTips for Finding Software Engineer Jobs at Venture Global LNG Jobs
Frame your skills around industrial software systems
Venture Global LNG prioritizes engineers who can work with SCADA, control systems, or operational technology alongside traditional software development. Tailor your resume to highlight any experience with energy infrastructure, industrial automation, or real-time data pipelines before you apply.
Request the LCA before your start date
Your employer files a Labor Condition Application with the DOL before your visa petition can move forward. Ask your HR contact to confirm LCA certification is underway early in the offer stage so it does not create a gap between your accepted offer and your actual start date.
Secure documentation of your specialty occupation status
USCIS scrutinizes Software Engineer petitions from energy companies to confirm the role requires a specific technical degree. Gather course transcripts and job description language that links your degree field directly to the systems engineering work Venture Global LNG performs.
Target open roles through Migrate Mate
Search for Software Engineer openings at Venture Global LNG on Migrate Mate, which filters jobs by visa sponsorship type so you can identify active roles that match your H-1B or E-3 status before investing time in the application process.
Account for project-based hiring cycles in energy
LNG companies like Venture Global often staff up ahead of major facility commissioning phases. Monitoring job postings tied to new terminal projects gives you a practical signal of when Software Engineer headcount is likely to open and sponsorship bandwidth is highest.
Software Engineer at Venture Global LNG jobs are hiring across the US. Find yours.
Find Software Engineer at Venture Global LNG JobsFrequently Asked Questions
Does Venture Global LNG sponsor H-1B visas for Software Engineers?
Yes, Venture Global LNG has a documented history of sponsoring H-1B visas for Software Engineer roles. The company files petitions through the standard USCIS H-1B process, which includes DOL Labor Condition Application certification. Because H-1B is subject to an annual lottery, your petition must be submitted during the registration window each spring for a potential October start date.
Which visa types are commonly used for Software Engineer roles at Venture Global LNG?
Software Engineers at Venture Global LNG are sponsored under both the H-1B and E-3 visa categories. H-1B is available to nationals of any country but requires surviving the annual USCIS lottery. The E-3 is exclusive to Australian citizens, has its own separate allocation, and can be filed year-round without a lottery, making it a faster path for eligible candidates.
What qualifications are expected for Software Engineer positions at Venture Global LNG?
Venture Global LNG generally looks for Software Engineers with a bachelor's degree or higher in computer science, software engineering, or a closely related technical field. Practical experience with industrial systems, data infrastructure, or operational technology is a meaningful differentiator given the company's LNG production environment. USCIS also requires the role to qualify as a specialty occupation, so your degree field should align directly with the position's core duties.
How do I apply for Software Engineer jobs at Venture Global LNG?
You can browse current Software Engineer openings at Venture Global LNG on Migrate Mate, which surfaces roles filtered by visa sponsorship type so you can confirm H-1B or E-3 eligibility upfront. Once you identify a suitable role, apply through Venture Global LNG's careers page and indicate your visa sponsorship needs early in recruiter communications to avoid surprises later in the process.
How long does the visa sponsorship process take for a Software Engineer at Venture Global LNG?
For H-1B, the full timeline from USCIS registration in March to an October 1 start date is roughly six to seven months, assuming lottery selection. Premium processing can reduce USCIS adjudication to around 15 business days once the petition is filed. For E-3, consular processing at an Australian embassy typically takes two to four weeks after the employer secures DOL LCA certification, making it significantly faster for eligible candidates.
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