Machine Learning Jobs in Austin, TX

Positions 33,486 Updated daily

Looking for Machine Learning jobs in Austin, TX? Browse our curated listings with transparent salary information to find the perfect Machine Learning position in the Austin, TX area.

Registered Nurse

Company: DaVita

Location: Deer Park, TX

Posted Jan 30, 2025

Operations Training and Development Manager

Company: Kodiak Robotics

Location: Dallas-Fort Worth, TX

Posted Jan 30, 2025

Kodiak Robotics Inc, founded in 2018, is a leading company in autonomous ground transportation, focusing on driverless military and long-haul trucking applications. They are seeking an Operations Training and Development Manager based in Lancaster, TX, to design, implement, and evaluate training programs. The role involves assessing training needs, developing materials, coordinating sessions, and maintaining training records. The company offers a competitive compensation package, excellent benefits, and a commitment to diversity and equal opportunity employment.

Lead Machine Learning Ops Engineer

Company:

Location: Katy, TX

Posted Jan 30, 2025

Engineering Director

Company: Sonar

Location: Austin, TX

Posted Jan 30, 2025

Sonar is seeking an experienced Engineering Director to lead their Engineering Team and drive the development of their products. The role involves providing technical leadership, defining the technical direction and roadmap, collaborating with product management, ensuring high-quality software products, and fostering a culture of innovation and excellence. Sonar values a dynamic work culture that embraces diversity, work-life balance, and continuous learning. They are committed to creating a diverse work environment and are an equal opportunity employer.

AVP, Employment Counsel

Company: Revantage, a Blackstone Portfolio Company

Location: Dallas-Fort Worth, TX

Posted Jan 30, 2025

Revantage, a Blackstone Real Estate portfolio company, is a global provider of corporate services with a commitment to collaboration and inclusivity. The company offers value-added services and world-class talent across diverse asset classes. Headquartered in Chicago, Revantage's footprint extends across North America, Europe, and Asia Pacific. The company values its people, fostering a workplace where everyone can be themselves and do their best work. The Assistant Vice President, Employment Counsel, will provide day-to-day support to Revantage and Blackstone portfolio company HR Business Partners on employment law, employee policies, and compliance. The role requires a Juris Doctorate, active license to practice in Illinois or Texas, and at least 5 years of relevant experience. The position offers competitive compensation, work-life balance, and learning opportunities.

Phlebotomist

Company: CSL

Location: Houston, TX

Posted Jan 30, 2025

Lead Machine Learning Ops Engineer

Company:

Location: Houston, TX

Posted Jan 30, 2025

Sr. Manager, Cloud Engineering

Company: Q2

Location: Austin, TX

Posted Jan 30, 2025

Q2 is a global provider of mobile banking platforms and technology solutions, serving over 22 million end users across 1300 financial institutions and fintech clients. The company is passionate about its mission to build strong, diverse communities by strengthening their financial institutions. Q2 invests in its employees through ongoing learning opportunities, mentorship programs, and internal mobility. The company also fosters a culture of continuous improvement, innovation, and high performance. They are currently seeking a Cloud Engineering Operations Sr Manager to oversee the deployment, maintenance, and optimization of AWS Cloud, Azure Cloud, and data center infrastructure. The role requires expertise in cloud operations, incident management, and team leadership. The manager will ensure reliable, secure, and cost-effective service delivery, meeting operational requirements. This is an exciting opportunity to be on the cutting edge of service management practices within a rapidly growing organization.

Manufacturing Engineer

Company:

Location: Lubbock, TX

Posted Jan 30, 2025

Lead Machine Learning Ops Engineer

Company:

Location: Cypress, TX

Posted Jan 30, 2025

Lead Machine Learning Ops Engineer

Company:

Location: Houston, TX

Posted Jan 30, 2025

Frequently Asked Questions

What are typical salary ranges by seniority for machine learning roles?
Entry‑level ML Engineer: $90k–$120k; Mid‑level ML Engineer or Data Scientist: $120k–$160k; Senior ML Engineer or Research Scientist: $160k–$220k; Lead ML Engineer or Principal Research Scientist: $200k–$280k; AI Product Manager: $130k–$180k depending on experience and market.
What skills and certifications are most valuable in machine learning today?
Core language: Python; Deep learning frameworks: TensorFlow, PyTorch; Scikit‑learn for classical models; SQL and NoSQL databases for data ingestion; Docker and Kubernetes for deployment; Cloud AI services such as AWS SageMaker, GCP Vertex AI, Azure ML. Certifications: TensorFlow Developer Certificate, AWS Certified Machine Learning – Specialty, GCP Professional Machine Learning Engineer.
How common is remote work for machine learning positions?
Over 70% of ML roles allow full remote or hybrid arrangements. Startups and fintech firms tend to offer 100% remote options, while larger enterprises often provide hybrid models with occasional on‑site data‑center visits. Remote work is especially prevalent for roles focused on model training and research.
What career progression paths exist in machine learning?
Typical paths: ML Engineer → Senior ML Engineer → Lead ML Engineer → ML Manager; Data Scientist → Senior Data Scientist → Lead Data Scientist → Head of Data; Research Scientist → Senior Research Scientist → Principal Scientist → Chief Data Scientist; ML Ops Engineer → Senior ML Ops Engineer → Lead ML Ops Engineer → Director of MLOps. Progression often involves moving from coding to architecture, then to leadership and strategy.
What are the current industry trends shaping machine learning hiring?
Key trends: reinforcement learning for autonomous systems; federated learning for privacy‑preserving models; edge AI for IoT devices; AutoML platforms speeding model deployment; MLOps practices for scalable pipelines; explainable AI and ethics compliance; and increased demand for AI governance roles.

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