Machine Learning Jobs in Austin, TX

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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.

(USA) Tire & Battery Technician - Automotive

Company: Walmart

Location: Corpus Christi, TX

Posted Jan 25, 2025

View Details Apply on The Muse

Utility Worker

Company: Sodexo

Location: Cisco, TX

Posted Jan 25, 2025

View Details Apply on The Muse
bestinclass production facilities energetic resultsdriven individuals PharmaCann Human Resources team

Back of House Supervisor

Company: PharmaCann

Location: Dallas-Fort Worth, TX

Posted Jan 25, 2025

PharmaCann Inc is seeking a Back of the House Supervisor to manage inventory, ensure compliance, and lead a team in their dispensaries. The ideal candidate should have a Bachelor's degree, 2+ years of supervisory experience, and strong knowledge of retail technology. They will oversee inventory initiatives, ensure store compliance, and collaborate with cross-divisional teams. The role involves training, performance reviews, and maintaining professional documentation.

View Details Apply on BuiltIn

Coil Winder 3rd Shift

Company: Eaton

Location: Long Branch, TX

Posted Jan 25, 2025

View Details Apply on The Muse

Senior Systems Engineer

Company: Fidelity Investments

Location: Westlake, TX

Posted Jan 25, 2025

View Details Apply on The Muse

Portfolio Analyst

Company: Fisher Investments

Location: Plano, TX

Posted Jan 25, 2025

View Details Apply on The Muse

Summer Internship 2025-Navasota

Company: CRH

Location: Richards, TX

Posted Jan 25, 2025

View Details Apply on The Muse

Regional Sales Manager

Company: Thomson Reuters

Location: Frisco, TX

Posted Jan 25, 2025

View Details Apply on The Muse

Dialysis Experienced Registered Nurse

Company: DaVita

Location: San Antonio, TX

Posted Jan 25, 2025

View Details Apply on The Muse

(USA) Carwash/Gas Attendant

Company: Walmart

Location: Amarillo, TX

Posted Jan 25, 2025

View Details Apply on The Muse

Production Assembler - 3rd Shift (Onsite)

Company: RTX

Location: Allen, TX

Posted Jan 25, 2025

View Details Apply on The Muse

Retail Sales Associate - Sunset Valley

Company: Gap Inc.

Location: Austin, TX

Posted Jan 25, 2025

View Details Apply on The Muse

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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