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Contract Machine Learning Startup Jobs in Dallas, TX

Advent Global Solutions, Inc.

Sr. AI Engineer

Irving, TX · On-site

$100K - $137K/yr

... Contract to hire will need 3 months conversion waiver Location 3 days onsite in Irving, TX Sr. AI Engineer * Experience in software engineering, machine learning, artificial intelligence, or related ...

ADDSOURCE

Sr Lead Engineer - I_Azure

Irving, TX · On-site

... machine learning, document classification, validation frameworks, and intelligent automation. Roles and Responsibilities: Analyse invoice and contract variations across suppliers, countries ...

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Contract Machine Learning Startup information

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$29

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

As of Aug 17, 2026, the average hourly pay for contract machine learning startup in Dallas, TX is $48.41, according to ZipRecruiter salary data. Most workers in this role earn between $40.67 and $50.19 per hour, depending on experience, location, and employer.

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 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 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 popular job titles related to Contract Machine Learning Startup jobs in Dallas, TX?

For Contract Machine Learning Startup jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Contract Machine Learning Startup jobs in Dallas, TX look for?

The top searched job categories for Contract Machine Learning Startup jobs in Dallas, TX are:

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

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

Contract Machine Learning Startup jobs near you

Lead Applied AI & Machine Learning Engineer

JPMorgan Chase & Co.

Plano, TX • On-site

Full-time

Medical, Retirement

Posted 4 days ago

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 495 frontline employees who took The Breakroom Quiz

71st of 171 rated banks

Job description


Build what's next in enterprise AI-solutions that materially improve how teams make decisions, automate work, and serve internal customers. You will take generative AI from concept to production, help set the standard for semantic consistency across systems, and partner closely with stakeholders to turn complex business needs into measurable outcomes. You will mentor talent and influence technical direction across Corporate Technology and supported Corporate Functions.
As an Applied AI and Machine Learning Lead in the Corporate Technology Data Science and AI team, you will Build what's next in enterprise AI-solutions that materially improve how teams make decisions, automate work, and serve internal customers. In this role, you will take generative AI from concept to production and help set the standard for semantic consistency across systems. You will partner closely with stakeholders to turn complex business needs into measurable outcomes. You will mentor talent and influence technical direction across Corporate Technology and supported Corporate Functions. If you enjoy solving hard problems with real impact, this is the opportunity.
Job Responsibilities
  • Build generative AI, agentic AI, and large language model solutions in Python from proof of concept through production deployment with measurable outcomes
  • Design context engineering approaches to improve model accuracy, latency, reliability, and end-to-end user experience
  • Lead enterprise semantic modeling strategy, including ontology standards, governance practices, and lifecycle management
  • Partner with domain experts to create scalable ontologies that represent business entities, relationships, rules, and constraints
  • Define semantic integration patterns across data pipelines, application programming interfaces (APIs), data contracts, and experience layers to resolve semantic conflicts
  • Establish and govern a unified semantic layer that enables trusted analytics across business intelligence, machine learning, and transactional systems
  • Enable intelligent workflows and AI agents using ontology-driven context, semantic reasoning, and orchestration approaches
  • Build and maintain pipelines and frameworks for model training, evaluation, optimization, monitoring, and machine learning operations
  • Implement responsible AI practices, model risk controls, and governance aligned to regulated environments
  • Mentor engineers and data scientists, raising the bar on engineering rigor, reuse, and continuous improvement across the team

Required Qualifications, Capabilities, and Skills
  • Master's degree in a data science-related discipline and eight years of industry experience, or PhD in a data science-related discipline
  • Demonstrated experience developing and deploying machine learning and generative AI solutions using Python
  • Proven ability to write and maintain production-quality code, including documentation and maintainable design patterns
  • Experience building automated testing practices, including unit tests, and implementing continuous integration pipelines
  • Experience building and managing data pipelines and processing workflows for analytics and machine learning use cases
  • Strong scientific thinking and structured problem-solving skills, including hypothesis-driven analysis and metric definition
  • Strong written and verbal communication skills, with the ability to explain complex concepts to technical and non-technical stakeholders
  • Demonstrated ownership and attention to detail when operating in ambiguous, complex problem spaces
  • Ability to work independently while collaborating effectively across product, engineering, data, and business partners

Preferred Qualifications, Capabilities, and Skills
  • Experience designing or governing semantic models and ontologies, including taxonomy design and lifecycle governance
  • Experience implementing retrieval-augmented generation, tool use, and evaluation strategies for large language model applications
  • Familiarity with responsible AI techniques, including bias testing, explainability approaches, and model monitoring standards
  • Experience designing scalable architectures for real-time or near-real-time inference and intelligent workflow orchestration
  • Experience influencing cross-functional technical direction and mentoring engineers through design reviews and delivery execution

#LI-RB3
About Us
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
About the Team
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.

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