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Contract Machine Learning Startup Jobs in Houston, TX

... agroscience Contract Research Organisation services. Eurofins is one of the market leaders in ... Support installation, startup, and deployment activities. Drive Enterprise Improvements * Evaluate ...

... agroscience Contract Research Organisation services. Eurofins is one of the market leaders in ... Support installation, startup, and deployment activities. Drive Enterprise Improvements * Evaluate ...

... science, machine learning, and artificial intelligence solutions for industrial and production ... NOT a contract. EQUAL EMPLOYMENT OPPORTUNITY & VETERANS Company policy is to provide every ...

New

Manage vendor relationships, support contracts, and technology partnerships. * Lead cross-functional project teams delivering strategic AI initiatives. Technical Skills AI & Machine Learning * Azure ...

Data Engineer

Houston, TX ยท On-site

$109K - $131K/yr

This is a Contract Opportunity with our company that MUST be worked on a W2 Only. No C2C ... machine learning solutions. The ideal candidate can work independently, solve complex technical ...

Showing results 21-40

Contract Machine Learning Startup information

See Houston, TX salary details

$28

$46

$94

How much do contract machine learning startup jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for contract machine learning startup in Houston, TX is $46.73, according to ZipRecruiter salary data. Most workers in this role earn between $39.23 and $48.41 per hour, depending on experience, location, and employer.

What is a contract machine learning startup?

A Contract Machine Learning Startup is a company or team that provides machine learning solutions and services to clients on a contract basis. Instead of developing their own products, these startups typically work with other businesses to build custom machine learning models, analyze data, and help integrate AI technologies into existing workflows. They may offer expertise in areas such as natural language processing, computer vision, or predictive analytics, and usually operate on short-term or project-based contracts. This approach allows client companies to access specialized knowledge without hiring full-time data scientists or engineers.

What are the key skills and qualifications needed to thrive in a contract machine learning startup role?

Success in a Contract Machine Learning Startup role generally requires expertise in machine learning algorithms, data analysis, and a solid background in computer science or related fields. Familiarity with programming languages such as Python or R, experience with ML frameworks like TensorFlow or PyTorch, and knowledge of cloud platforms (e.g., AWS, GCP) are typically expected. Strong problem-solving, adaptability, and effective communication help professionals collaborate with clients and respond to rapidly changing project requirements. These skills and qualities are vital to deliver innovative, scalable solutions in fast-paced, outcome-driven startup environments.

What are some common challenges faced by machine learning professionals working on a contract basis at startups?

Machine learning professionals working as contractors at startups often face challenges such as rapidly changing project scopes, limited access to large datasets, and the need to quickly adapt to new tools and frameworks. Startups typically move fast, so contractors must be comfortable with ambiguity and prioritize delivering value in short timeframes. Additionally, they may need to collaborate closely with cross-functional teams, such as product managers and engineers, to ensure that machine learning solutions align with business goals.

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

AspectContract Machine Learning StartupData Scientist
CredentialsRelevant degrees, certifications in ML/AITypically similar credentials, often with advanced degrees
Work EnvironmentProject-based, startup setting, flexible hoursOffice or remote, corporate or research settings
Employer & IndustryStartups in tech, AI, or data-driven sectorsVaried industries including tech, finance, healthcare
Search & Comparison IntentUnderstanding contract roles in ML startupsExploring data science career options

Contract Machine Learning Startup roles focus on short-term, project-based work within startup environments, often requiring specialized skills in ML and AI. Data Scientists typically work in more established companies or research settings, with similar credentials but often in a full-time capacity. Both roles demand strong technical backgrounds, but contract roles offer flexibility and varied projects, while Data Scientists may have more stability and broader responsibilities.

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

The most popular types of Machine Learning Startup jobs in Houston, TX are:

What cities near Houston, TX are hiring for Contract Machine Learning Startup jobs?

Cities near Houston, TX with the most Contract Machine Learning Startup job openings:

Software Engineer, Generalist in Autonomous Driving System

Worky

Houston, TX โ€ข On-site

$95 - $150/hr

Other

Posted 17 days ago


Key responsibilities

  • Design, implement, test, and maintain software features under the guidance of experienced engineers.

  • Build user-facing applications, backend services, APIs, data pipelines, or internal engineering tools.

  • Debug software issues and help improve system reliability, performance, usability, and observability.


Job description

About the Role

At Bot Auto, we are revolutionizing the transportation of goods through autonomous trucking. With the agility of a startup and the experience of a team that has achieved numerous industry firsts, we build technology that connects autonomous vehicles, cloud infrastructure, data, machine learning, and real-world fleet operations.

We are looking for curious and motivated software engineers to help build the systems that make autonomous trucking possible.

Depending on your interests, experience, and business needs, you may work on one or more areas, including:

  • Full-stack and operational applications
  • Distributed systems and backend services
  • Developer and core infrastructure platforms
  • Data processing and workflow orchestration
  • Machine learning infrastructure
  • Simulation and evaluation applications
  • Build, release, and deployment tooling

You do not need prior experience in every area. We are looking for engineers with strong fundamentals, an eagerness to learn, and the ability to solve practical problems collaboratively. You will work alongside experienced engineers and develop expertise through real projects that directly support our autonomous vehicles and operations.

Key Responsibilities
  • Design, implement, test, and maintain software features under the guidance of experienced engineers.
  • Build user-facing applications, backend services, APIs, data pipelines, or internal engineering tools.
  • Develop responsive web interfaces using technologies such as React and TypeScript.
  • Build backend services and workflow automation, primarily using Python and, where appropriate, Go.
  • Work with databases, event-driven systems, and real-time data to connect applications, infrastructure, and autonomous vehicle operations.
  • Contribute to platforms supporting areas such as fleet operations, simulation, machine learning, data processing, CI/CD, and software deployment.
  • Debug software issues and help improve system reliability, performance, usability, and observability.
  • Write clean, maintainable, well-tested, and well-documented code.
  • Participate in code reviews, technical discussions, testing, deployment, and production support.
  • Collaborate with engineers, product managers, autonomy teams, and operations teams to translate real-world needs into dependable software.
  • Learn new technologies and engineering practices as your responsibilities grow.
Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
  • 0-3 years of professional software engineering experience. New graduates with strong academic, internship, open-source, or personal project experience are encouraged to apply.
  • Programming proficiency in at least one general-purpose language, preferably Python, Go, JavaScript/TypeScript, Java, or C++.
  • Solid understanding of software engineering fundamentals, including data structures, algorithms, debugging, testing, and source control.
  • Ability to break down problems, learn unfamiliar systems, and deliver well-scoped work.
  • Strong written and verbal communication skills.
  • Collaborative mindset, attention to detail, and willingness to receive and apply feedback.
Preferred Qualifications

Experience in one or more of the following areas is helpful but not required:

  • Full-stack web development using React, TypeScript, and modern frontend tooling.
  • Backend service or API development using Python or Go.
  • SQL or NoSQL databases.
  • Distributed systems, asynchronous processing, or event-driven architectures.
  • Data processing, batch workflows, or workflow orchestration systems.
  • Machine learning pipelines, model evaluation, experiment tracking, annotation, or dataset management.
  • Simulation, visualization, geospatial applications, or real-time operational interfaces.
  • Docker, Kubernetes, or cloud platforms such as AWS.
  • CI/CD systems, build tools, package management, or developer productivity tooling.
  • Streaming and messaging technologies such as NATS, Kafka, MQTT, or WebSockets.
  • Observability tools such as metrics, logging, tracing, dashboards, or alerting.
  • Autonomous vehicles, robotics, transportation, logistics, or other systems that interact with the physical world.
What We Value
  • Strong engineering fundamentals over familiarity with a particular technology stack.
  • Demonstrated ability to build, debug, or improve working software.
  • Curiosity about how systems work across application, infrastructure, and operational boundaries.
  • Ownership of your work while knowing when to ask for help.
  • Thoughtful consideration of reliability, usability, maintainability, and real-world impact.
  • Interest in growing into a versatile engineer who can contribute across multiple technical domains.

At Bot Auto, engineers are not limited to isolated tasks. You will contribute to production systems, learn from experienced teammates, and have opportunities to explore different engineering areas as the company and your career grow.

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