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Director Machine Learning Jobs in Dallas, TX (NOW HIRING)

Smash CR

Director of AI/ML (P-161)

Flower Mound, TX · On-site

Drive implementation of machine learning, generative AI, and multi-agent orchestration solutions. * Oversee development and deployment of AI-powered automation initiatives using Microsoft Power ...

Smash CR

Director of AI/ML (P-161)

Flower Mound, TX · On-site

Drive implementation of machine learning, generative AI, and multi-agent orchestration solutions. * Oversee development and deployment of AI-powered automation initiatives using Microsoft Power ...

Integra

Director Electrical Engineering

Dallas, TX · On-site +1

Lead engineering efforts supporting NVIDIA GPU clusters, AI training environments, machine learning ... direct-to-chip cooling applications, , high-density racks exceeding 50 kW, 80 kW, and 120+ kW ...

One Network Enterprises

Product Director

Dallas, TX · On-site

$120 - $180/hr

Powered by NEO, One Network's machine learning and intelligent agent technology, it enables ... The Director Product will be a member of the Product Management team for One Network Supply Chain ...

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All JobsMachine Learning JobsDirector Machine Learning JobsDirector Machine Learning Jobs in Dallas, TX

Director Machine Learning information

See Dallas, TX salary details

$35.8K

$91.3K

$140.1K

How much do director machine learning jobs pay per year?

As of Sep 7, 2026, the average yearly pay for director machine learning in Dallas, TX is $91,330.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,000.00 and $105,300.00 per year, depending on experience, location, and employer.

What is a director machine learning?

A Director of Machine Learning leads teams in developing and deploying machine learning models to solve business challenges. They define the AI strategy, oversee research, and ensure models are scalable and ethical. This role requires expertise in machine learning, data science, and leadership, as well as collaboration with cross-functional teams. Directors also stay updated on industry advancements and drive innovation within their organizations.

What are the primary responsibilities and challenges faced by a director machine learning on a daily basis?

A Director of Machine Learning is typically responsible for overseeing the development and deployment of machine learning solutions, mentoring technical teams, setting strategic direction for AI initiatives, and ensuring the alignment of projects with organizational goals. Challenges often include balancing innovative research with business priorities, navigating evolving technology landscapes, and coordinating efforts across data science, engineering, and stakeholder teams. This role requires regular collaboration with product managers, executives, and cross-functional departments to prioritize initiatives and communicate complex technical concepts. Successful directors excel at fostering a culture of continuous learning, optimizing team productivity, and staying ahead in a fast-paced, rapidly changing field.

What are the key skills and qualifications needed to thrive in the director machine learning position, and why are they important?

To thrive as a Director Machine Learning, you need advanced expertise in machine learning, statistics, data science, and leadership, typically supported by a master's or Ph.D. in a related field and several years of relevant industry experience. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and data management systems, as well as certifications like AWS Certified Machine Learning or Google Professional Machine Learning Engineer, are commonly required. Exceptional communication, strategic thinking, and team management skills distinguish top candidates in this role. These capabilities are essential for driving organizational AI initiatives, fostering high-performing teams, and delivering impactful business solutions.

Is a machine learning director a high paying job?

A machine learning director typically earns a high salary due to the specialized skills, leadership responsibilities, and experience required for the role. Compensation often includes base salary, bonuses, and stock options, reflecting the demand for expertise in AI and data science. Salaries can vary based on industry, company size, and location, but generally rank among the higher-paying technology leadership positions.

What does a director of machine learning do?

A director of machine learning oversees the development and implementation of machine learning strategies and projects within an organization. They lead teams of data scientists and engineers, set technical goals, ensure project alignment with business objectives, and often collaborate with other departments to integrate AI solutions using tools like Python, TensorFlow, or PyTorch.

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

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

What are popular job titles related to Director Machine Learning jobs in Dallas, TX?

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

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

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

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

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

Director Machine Learning jobs near you
Infographic showing various Director Machine Learning job openings in Dallas, TX as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $91,330 per year, or $43.9 per hour.

Director of AI/ML (P-161)

Smash CR

Flower Mound, TX • On-site

Full-time

Re-posted 28 days ago

Job description

SMASH, Who we are?
We believe in long-lasting relationships with our talent. We invest time getting to know them and understanding what they seek as their professional next step.
We aim to find the perfect match. As agents, we pair our talent with our US clients, not only by their technical skills but as a cultural fit. Our core competency is to find the right talent fast.
This role is available to candidates located within the United States. Applicants must be U.S. citizens or hold a valid U.S. work authorization to be considered.
Hybrid role: onsite 2 days per week. Flower Mound, TX
Role summary
You will lead the enterprise AI/ML and intelligent automation strategy, driving the design and operationalization of scalable AI solutions across the organization's data platform. This role combines technical leadership, AI architecture expertise, and cross-functional collaboration to deliver machine learning, generative AI, multi-agent systems, and automation initiatives that create measurable business value.
Responsibilities
  • Define and execute the enterprise AI/ML and intelligent automation strategy.
  • Lead and mentor teams of AI engineers, ML engineers, and automation developers.
  • Design scalable, secure, and governed AI architectures using Databricks and Microsoft technologies.
  • Drive implementation of machine learning, generative AI, and multi-agent orchestration solutions.
  • Oversee development and deployment of AI-powered automation initiatives using Microsoft Power Automate and Copilot technologies.
  • Collaborate with Data Engineering, Reporting, and business teams to operationalize AI capabilities.
  • Implement AI governance, model lifecycle management, and responsible AI best practices.
  • Lead adoption of Databricks AI capabilities including MLflow, model serving, and conversational AI solutions.
  • Integrate AI and automation systems with enterprise applications such as ERP, CRM, and logistics platforms.
  • Establish KPIs and performance metrics to measure AI and automation impact.
  • Drive continuous innovation and evaluate emerging AI technologies and frameworks.
  • Communicate AI strategy, risks, and business outcomes to executive stakeholders.

Requirements - Must-haves
  • Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field (or equivalent experience).
  • 10+ years of experience in AI, machine learning, automation, or related technical domains.
  • 5+ years of leadership experience managing technical or engineering teams.
  • Experience leading enterprise AI and automation initiatives using Databricks and Microsoft technologies.
  • Strong expertise in enterprise AI architecture and machine learning platform design.
  • Experience implementing generative AI and agent-based systems.
  • Hands-on experience with Databricks AI capabilities including MLflow and model serving.
  • Experience integrating AI capabilities with Microsoft Copilot platforms.
  • Strong communication, stakeholder management, and leadership skills.
  • Ability to drive scalable, secure, and governed AI solutions.

Nice-to-haves (optional)
  • Experience with Microsoft Power Automate and robotic process automation (RPA).
  • Experience with conversational AI platforms such as Databricks Genie.
  • Experience implementing multi-agent orchestration frameworks.
  • Experience integrating AI systems with ERP, CRM, or logistics platforms.
  • Experience with AI-powered image or video processing technologies.
  • 12-15 years of progressive experience in AI engineering or enterprise data platforms.

Apply