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Full Time Machine Learning Engineer New Grad Jobs in Houston, TX

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow ... new integrations, data connectors, and domain-specific prompt engineering; work closely with ...

Vitol

Senior Machine Learning Engineer

Houston, TX

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow ... new integrations, data connectors, and domain-specific prompt engineering; work closely with ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$116K - $154K/yr

... new integrations, data connectors, and domain-specific prompt engineering; work closely with ... machine learning or statistical models, with a proven track record of delivering end-to-end ...

Crowe LLP

Machine Learning Engineer

The Woodlands, TX · On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

Crowe LLP

Machine Learning Engineer

Houston, TX · On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

NobleAI

Lead Machine Learning Engineer

Houston, TX · On-site +1

$97K - $128K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI, you will be responsible for architecting, building, and deploying intelligent features to our VIP ...

NobleAI

Lead Machine Learning Engineer

Houston, TX · Remote

$104K - $138K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI, you will be responsible for architecting, building, and deploying intelligent features to our VIP ...

NobleAI

Lead Machine Learning Engineer

Houston, TX · On-site +1

$97K - $128K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI, you will be responsible for architecting, building, and deploying intelligent features to our VIP ...

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All JobsMachine Learning Engineer New Grad JobsFull Time Machine Learning Engineer New Grad JobsFull Time Machine Learning Engineer New Grad Jobs in Houston, TX

Full Time Machine Learning Engineer New Grad information

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$123K

$184.8K

How much do full time machine learning engineer new grad jobs pay per year?

As of Aug 28, 2026, the average yearly pay for full time machine learning engineer new grad in Houston, TX is $122,971.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,900.00 and $148,000.00 per year, depending on experience, location, and employer.

What does a full time machine learning engineer new grad do?

A Full Time Machine Learning Engineer New Grad is an entry-level professional who designs, builds, and deploys machine learning models as part of a technical team. They often work on tasks such as data preprocessing, developing and testing algorithms, and integrating models into production systems. New grad engineers usually collaborate with data scientists, software engineers, and product teams to solve real-world problems using machine learning. Their responsibilities also include staying updated with the latest advancements in the field and learning best practices for model development and deployment.

What are the key skills and qualifications needed to thrive as a full time machine learning engineer new grad, and why are they important?

To excel as a Full Time Machine Learning Engineer New Grad, you typically need a solid background in computer science, statistics, and mathematics, often demonstrated through a relevant degree or coursework. Familiarity with programming languages like Python, and experience with machine learning libraries such as TensorFlow or PyTorch, as well as tools for data analysis and version control, are essential. Strong problem-solving abilities, effective communication, and a willingness to learn new technologies help new grads stand out in collaborative and fast-paced environments. These skills and qualities are crucial for building effective models, working well within teams, and adapting to the rapidly evolving field of machine learning.

What are some common challenges new graduates face when transitioning into a full-time machine learning engineer role?

New graduates entering a full-time Machine Learning Engineer position often encounter challenges such as adapting to large-scale production systems, collaborating with cross-functional teams, and bridging the gap between academic projects and real-world business problems. Unlike school assignments, industry projects require scalable, maintainable code and thorough documentation. Additionally, new grads must quickly learn to communicate their technical findings to non-technical stakeholders and prioritize tasks amid fast-paced development cycles.

What is the difference between Full Time Machine Learning Engineer New Grad vs Data Scientist New Grad?

AspectFull Time Machine Learning Engineer New GradData Scientist New Grad
Required CredentialsBachelor's in CS, Math, or related; some internshipsBachelor's in Statistics, CS, or related; some internships
Work EnvironmentDeveloping ML models, deploying algorithms, coding in Python/C++Analyzing data, creating reports, statistical modeling
Industry UsageTech, finance, healthcare, focusing on ML systemsTech, marketing, finance, focusing on data analysis

Full Time Machine Learning Engineer New Grad roles focus on building and deploying machine learning models, requiring coding and engineering skills. Data Scientist New Grad roles emphasize data analysis, statistical modeling, and insights. Both roles often share similar educational backgrounds but differ in daily tasks and technical focus.

Are full time machine learning engineers still in demand?

Full time machine learning engineers are currently in high demand due to the growth of AI applications across industries. Employers seek professionals skilled in programming, data analysis, and tools like Python, TensorFlow, and PyTorch to develop and deploy machine learning models. The role remains a strong career choice with competitive salaries and opportunities for advancement.

What are the most commonly searched types of Machine Learning Engineer New Grad jobs in Houston, TX?

The most popular types of Machine Learning Engineer New Grad jobs in Houston, TX are:

What are popular job titles related to Full Time Machine Learning Engineer New Grad jobs in Houston, TX?

For Full Time Machine Learning Engineer New Grad jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Full Time Machine Learning Engineer New Grad jobs in Houston, TX look for?

The top searched job categories for Full Time Machine Learning Engineer New Grad jobs in Houston, TX are:

Full Time Machine Learning Engineer New Grad jobs near you
Infographic showing various Full Time Machine Learning Engineer New Grad job openings in Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $122,971 per year, or $59.1 per hour.

Senior Machine Learning Engineer

Vitol

Houston, TX • On-site

$117K - $154K/yr

Full-time

Re-posted 21 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