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Contract Machine Learning Software Engineer Jobs in Texas

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The individual will work closely with the data and machine learning specialists, software engineers and commercial teams to deliver machine learning models and applications. We work across the ...

Intuit

Staff Machine Learning Engineer

Plano, TX

Overview Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside ... Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ...

Intuit

Staff Machine Learning Engineer

Plano, TX · On-site

Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI ... Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The individual will work closely with the data and machine learning specialists, software engineers and commercial teams to deliver machine learning models and applications. We work across the ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The individual will work closely with the data and machine learning specialists, software engineers and commercial teams to deliver machine learning models and applications. We work across the ...

Neuralink

Machine Learning Engineer

Austin, TX

The BCI team develops the software and systems that communicate with the brain. These systems ... About the Role: Engineers on the BCI team utilize signal processing and machine learning to ...

Cymertek

Software Engineer

San Antonio, TX

... Machine Learning Engineer, AI Engineer, Robotics Software Engineer, etc. DEGREE (Level Desired ... Most contracts allow additional experience (4-5 years) in lieu of a Bachelor's Degree. Some ...

Cymertek

Software Engineer

San Antonio, TX · On-site

... Machine Learning Engineer, AI Engineer, Robotics Software Engineer, etc. DEGREE (Level Desired ... Most contracts allow additional experience (4-5 years) in lieu of a Bachelor's Degree. Some ...

Compunnel

Machine Learning Engineer

Plano, TX · On-site

Job Summary We are seeking a Machine Learning Engineer with strong expertise in machine learning model development, data engineering, and modern cloud-based analytics platforms. This role will focus ...

Cymertek

Software Engineer

San Antonio, TX

... Machine Learning Engineer, AI Engineer, Robotics Software Engineer, etc. DEGREE (Level Desired ... Most contracts allow additional experience (4-5 years) in lieu of a Bachelor's Degree. Some ...

Q2 Software, Inc.

Machine Learning Engineer

Austin, TX · On-site

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

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All JobsContract Machine Learning Software Engineer JobsContract Machine Learning Software Engineer Jobs in Texas

Contract Machine Learning Software Engineer information

How does a Contract Machine Learning Software Engineer typically collaborate with full-time team members during a project?

As a Contract Machine Learning Software Engineer, you will often work closely with full-time data scientists, software engineers, and product managers. Collaboration usually happens through regular stand-up meetings, code reviews, and shared documentation platforms. Despite being a contractor, you’re expected to integrate seamlessly with the team, communicate progress transparently, and adapt to the company’s workflows. Building strong relationships and proactively seeking feedback can help ensure your contributions align with the project’s goals and timelines.

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

AspectContract Machine Learning Software EngineerData Scientist
CredentialsBachelor's or Master’s in CS, ML, or related fields; experience with ML frameworksBachelor's or Master’s in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentProject-based, often remote, focused on developing ML models and softwareData analysis, visualization, and interpretation, often in research or business settings
Employer & Industry UsageTech companies, startups, consulting firms; used for deploying ML solutionsResearch institutions, finance, healthcare, and tech; used for insights and decision-making

The main difference is that Contract Machine Learning Software Engineers focus on developing and deploying ML models as software solutions, while Data Scientists analyze data to generate insights. Both roles require strong technical skills, but their primary objectives and work environments differ.

Which 5 jobs will survive AI?

For a Contract Machine Learning Software Engineer, roles that involve complex problem-solving, creativity, and human judgment are more likely to persist, such as AI research, data science, cybersecurity, software architecture, and technical consulting. These jobs require specialized skills, domain expertise, and adaptability that AI tools currently cannot fully replicate. Continuous learning and proficiency with AI and machine learning tools will help maintain relevance in this evolving field.

What engineers make $500,000?

Senior machine learning software engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or at large tech companies can earn $500,000 or more annually. Compensation may include base salary, bonuses, and stock options, especially in competitive markets or executive-level roles.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer or AI research director, often involving advanced skills in deep learning, data science, and software engineering. These roles usually require extensive experience, specialized knowledge, and may include leadership responsibilities or working with cutting-edge AI technologies. Compensation at this level reflects the complexity and impact of the work, often including bonuses and stock options.

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

To thrive as a Contract Machine Learning Software Engineer, you need a strong background in computer science, proficiency in programming languages like Python, and expertise in machine learning algorithms, typically supported by a relevant degree or equivalent experience. Familiarity with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, along with knowledge of version control systems like Git, is essential. Strong problem-solving abilities, communication skills, and the ability to work independently or with cross-functional teams make someone stand out in this role. These skills ensure efficient delivery of scalable machine learning solutions that meet client requirements and project timelines.

How much do contract software engineers make?

Contract machine learning software engineers typically earn between $50 and $150 per hour, depending on experience, location, and project complexity. Rates can vary based on skills in specific frameworks, tools, and the duration of the contract.

What is a Contract Machine Learning Software Engineer?

A Contract Machine Learning Software Engineer is a professional who is hired on a temporary or project basis to design, develop, and deploy machine learning models and systems. They often work with organizations that need specialized expertise for a limited duration, helping to build algorithms, analyze data, and integrate AI solutions into existing software products. Contract engineers typically have strong backgrounds in programming, mathematics, and data science, and they may work remotely or on-site. Their responsibilities can range from data preprocessing and model training to deploying models in production environments. This arrangement allows companies to access advanced machine learning skills without committing to a full-time hire.
What are the most commonly searched types of Machine Learning Software Engineer jobs in Texas? The most popular types of Machine Learning Software Engineer jobs in Texas are:
What cities in Texas are hiring for Contract Machine Learning Software Engineer jobs? Cities in Texas with the most Contract Machine Learning Software Engineer job openings:
Contract Machine Learning Software Engineer jobs near you

Senior Machine Learning Engineer

Vitol

Houston, TX • On-site

$117K - $154K/yr

Full-time

Posted 10 days ago

Job description

Company Description
Vitol is an energy and commodities company with revenues of $400 billion in 2023; its primary business is the trading and distribution of energy products globally - it trades over seven million barrels per day of crude oil and products and, at any time, has 250 ships transporting its cargoes.
Vitol's clients include national oil companies, multinationals, leading industrial companies and utilities. Founded in Rotterdam in 1966, today Vitol serves clients from some 40 offices worldwide and is invested in energy assets globally including 16mm3 of storage, 480kbpd of refining capacity, and 7,000 service stations. To date, we have committed over $2.5 billion of capital to renewable projects, and are identifying and developing low-carbon opportunities around the world. Learn more about us here.
This Role is located in Houston, TX - In office 5x a week
Job Description
As our portfolio of work continues to grow, we are looking for an experienced Machine Learning Engineer to join our data science and machine learning team. The individual will work closely with the data and machine learning specialists, software engineers and commercial teams to deliver machine learning models and applications. We work across the trading business, operations, and other support functions; so the individual will need to be comfortable working with a variety of stakeholders and technologies.
The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing, exploratory analysis, model selection and tuning, and implementation of production models.
The successful candidate will join a team of experienced, collaborative practitioners, who are (pragmatically) solving some of the most challenging and impactful problems the energy industry is facing; as well as pushing the boundaries around the 'art of the possible'.
Core Responsibilities include:
  • Design, develop, and deploy end-to-end machine learning and data science solutions across our wider business activities (including trading, operations, and support functions) - from raw data ingestion through to production-grade models and monitoring
  • Drive adoption and development of the firm's internal GenAI chat platform as one of the technical leads, extending its capabilities through new integrations, data connectors, and domain-specific prompt engineering; work closely with trading desks and operational teams to identify high-value use cases, embed the tool into day-to-day workflows, and ensure outputs are robust, and trusted by end users.
  • Apply a broad range of modelling techniques - including time-series forecasting, NLP, classification, and generative AI - to commodity pricing, supply/demand signals, trade flow analysis, and operational optimization problems
  • Own the full data science lifecycle on assigned projects: data sourcing and cleaning, exploratory analysis, feature engineering, model selection and validation, deployment, and ongoing performance monitoring
  • Build and maintain robust, well-tested, production-quality code; contribute to shared infrastructure including ML pipelines, data orchestration, and model serving layers
  • Integrate ML and GenAI outputs into existing trading systems, dashboards, and workflows; work with software engineers to ensure reliable, scalable adoption across the business
  • Communicate analytical findings and model outputs clearly to non-technical stakeholders; present results, assumptions, and limitations in a manner that supports confident commercial decision-making
  • Actively participate in code reviews, experiment design, and tooling decisions; mentor colleagues and help raise the overall standard of analytical and engineering practice across the team

Qualifications
  • Master's degree or equivalent in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field
  • Fluency in Python for both data science and engineering purposes: clean, modular, well-documented code, with strong understanding of software engineering best practices including version control, testing, and code review
  • 5+ years of industry experience developing and deploying machine learning or statistical models, with a proven track record of delivering end-to-end solutions in production environments
  • Demonstrable experience applying a broad range of ML methodologies (supervised and unsupervised learning, time-series modelling, NLP/LLMs, optimization) to real-world business problems
  • Strong proficiency with ML frameworks (e.g. PyTorch, scikit-learn, Transformers) and experience building or consuming LLM-based pipelines and GenAI applications
  • Experience with cloud platforms (AWS preferred) and modern MLOps practices: containerization (Docker/Kubernetes), CI/CD, data pipeline orchestration (e.g. Airflow, Dagster), and model serving
  • Strong analytical and problem-solving ability: capable of defining and scoping open-ended problems, proposing sound methodological approaches, and defending modelling choices with rigorous reasoning
  • Excellent written and verbal communication skills, with the confidence to present model outputs, caveats, and commercial implications clearly to non-technical audiences including traders and senior management
  • Genuine intellectual curiosity about commodities markets, global energy flows, and the commercial dynamics of trading; willingness to develop domain knowledge as part of the role

Desirable Experience
  • Experience in the energy or commodities trading industry, with knowledge of financial markets and trading concepts
  • Experience surfacing ML outputs through interactive tools (e.g. Dash, Streamlit, or similar) and presenting use cases to non-technical audiences, including traders and senior management
  • Time-series modelling in a trading or financial context, including both ML-based and econometric approaches (e.g. ARIMA, cointegration, regime-switching models)
  • Data orchestrators (Airflow, Dagster) and cloud-based ETL/ELT pipelines

Additional Information
Personal Characteristics
  • A self-motivated individual who thrives on seeing the results of their work make an impact in the business
  • Pragmatic and delivery-focused: comfortable navigating ambiguity, balancing rigor with speed, and making sound judgements under uncertainty
  • Methodical and detail-oriented: rigorous in experimental design, data validation, and code quality, with a disciplined approach to documenting assumptions and results
  • Resourceful, able to think creatively and adapt in a dynamic environment
  • Team player, with an open non-political style and a high level of integrity
  • Desire to be a thought-partner in a fast-growing team, and make an impact at a business that sits at the heart of the world's energy flows

Work Environment
  • This job operates in a professional office environment. Because of the collaborative, fast-paced, and high energy nature of our business, Vitol requires team members to work from our fully-equipped office.

What we offer
  • Competitive salary and benefits package
  • Large diversity of projects with real-world impacts on a truly global scale
  • Entrepreneurial environment within a flat hierarchy, where great ideas come to life quickly
  • Close collaboration with various business units across our key regions (eg. London, Singapore, Houston, Geneva)
  • A highly motivated DS and ML team comprised of experienced individuals with a supportive attitude and great team spirit
  • Being part of the energy transition through increased emphasis on renewable & alternative energy sources at a pivotal moment in the industry
  • Strong management commitment to incorporating machine learning into the future of Vitol's operations

All your information will be kept confidential according to EEO guidelines.

Apply