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Contract Machine Learning Startup Jobs in Texas (NOW HIRING)

Lauretta AI LLC

Machine Learning Engineer L-1

Austin, TX · On-site

$80K - $93K/yr

... modules and machine learning models as part of an AI pipeline * Works with data and software ... Due to government contract requirements, applicants are able to get clearance are preferred

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX · On-site

$103.60K - $142.20K/yr

We are looking for a Senior Machine Learning Engineer II to contribute to the development and ... CesiumAstro does not accept unsolicited resumes from contract agencies or search firms. Any ...

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX · On-site

$103.60K - $142.20K/yr

We are looking for a Senior Machine Learning Engineer II to contribute to the development and ... CesiumAstro does not accept unsolicited resumes from contract agencies or search firms. Any ...

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX · On-site

$103.60K - $142.20K/yr

We are looking for a Senior Machine Learning Engineer II to contribute to the development and ... CesiumAstro does not accept unsolicited resumes from contract agencies or search firms. Any ...

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Contract Machine Learning Startup information

What are the key skills and qualifications needed to thrive in a Contract Machine Learning Startup role, and why are they important?

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 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 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 Texas? The most popular types of Machine Learning Startup jobs in Texas are:
What are popular job titles related to Contract Machine Learning Startup jobs in Texas? For Contract Machine Learning Startup jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Contract Machine Learning Startup jobs in Texas look for? The top searched job categories for Contract Machine Learning Startup jobs in Texas are:
What cities in Texas are hiring for Contract Machine Learning Startup jobs? Cities in Texas with the most Contract Machine Learning Startup job openings:
Contract Machine Learning Startup jobs near you

Machine Learning Engineer L-1

Lauretta AI LLC

Austin, TX • On-site

$80K - $93K/yr

Full-time

Posted 5 days ago

Job description

Job Description:
  • Develop high-quality, maintainable code to build and deploy computer vision modules and machine learning models as part of an AI pipeline
  • Works with data and software engineering team to integrate models into pipeline
  • Support construction and iteration of product prototypes
  • Support data pipeline engineering and automation
  • Stay up to date with state of the art developments in computer vision tasks
  • Other duties as required by supervisors
Additional Requirements:
  • Due to government contract requirements, applicants are able to get clearance are preferred
  • Experience working in MLOps and building pipelines for deploying ML models
  • Programming skills in Python, C/C++ or Javascript
  • Understanding of machine learning and deep learning fundamentals
  • Develop internal tooling as needed to support ML efforts
  • Production deployment and performance monitoring including code refactoring and optimization as needed
  • Support infrastructure engineering, security engineering, and architecture
  • Willing to learn and work well in a cross functional team environment
  • Fresh graduates are welcome to apply on a full-time basis

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