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Deep Learning Developer Jobs in Texas (NOW HIRING)

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX · On-site

$103K - $142K/yr

CesiumAstro is a developer and pioneer of communication systems for satellites and airborne ... Responsibilities : • Design, develop, and maintain deep learning pipelines for real-time data ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

We are looking for an experienced Senior Machine Learning Engineer with deep expertise in statistical and machine learning techniques, large-scale data processing, and model deployment in cloud ...

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX · On-site

$103K - $142K/yr

CesiumAstro is a developer and pioneer of innovative communication systems for satellites and ... Responsibilities : • Design, develop, and maintain deep learning pipelines for real-time data ...

TalentPros.AI

Staff Machine Learning Engineer

Austin, TX

$120K - $550K/yr

Demonstrated experience in deep learning and transformers models * Proficiency in frameworks like PyTorch or Tensorflow * Strong foundation in data structures, algorithms, and software engineering ...

Quarterhill

Machine Learning Engineer

Frisco, TX · On-site

Fine-tune and deploy computer vision and deep learning models for object detection, object tracking, and OCR at scale. * Develop vision-language models and Mixture of Experts architectures, from ...

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Deep Learning Developer information

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior Deep Learning Developer or AI research lead, often involving advanced skills in machine learning frameworks, data modeling, and programming. Such roles usually require extensive experience, specialized knowledge, and may include responsibilities like developing innovative AI solutions or leading AI teams in tech companies or research institutions.

What are the key skills and qualifications needed to thrive as a Deep Learning Developer, and why are they important?

To thrive as a Deep Learning Developer, you need a strong background in computer science, mathematics, and proficiency in programming languages like Python, often supported by a degree in a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, and experience with cloud platforms or GPU acceleration, are commonly required technical skills. Analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this role. These competencies are crucial for designing, training, and deploying advanced neural network models that address complex real-world problems.

What are Deep Learning Developers?

Deep Learning Developers are specialized software engineers or data scientists who design, build, and implement artificial intelligence systems using deep learning techniques. They work with neural networks, large datasets, and various frameworks like TensorFlow or PyTorch to develop models for tasks such as image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, optimization, and deployment to solve complex problems that require advanced pattern recognition. Deep Learning Developers often collaborate with AI researchers, data engineers, and product teams to integrate intelligent features into applications.

Which 3 jobs will survive AI?

Deep Learning Developers are likely to continue to be in demand as AI advances because they design and improve AI models, requiring specialized skills in programming, mathematics, and data analysis. Other roles expected to persist include AI ethics specialists and AI system trainers, as human oversight and ethical considerations remain essential. These jobs involve complex problem-solving and domain expertise that are difficult to fully automate.

What is the difference between Deep Learning Developer vs Machine Learning Engineer?

AspectDeep Learning DeveloperMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with neural networksBachelor's or Master's in CS, Data Science, or related; knowledge of algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural networksData-driven companies, software firms, industries applying machine learning
Industry UsagePrimarily in AI research, neural network development, deep learning projectsBroader application including predictive modeling, data analysis, and ML systems

Deep Learning Developers specialize in neural networks and deep learning models, often working on AI research and complex algorithms. Machine Learning Engineers have a broader focus on developing, deploying, and maintaining machine learning models across various applications. While both roles require similar educational backgrounds, their focus areas and industry applications differ.

What are some common challenges Deep Learning Developers face when deploying models to production environments?

Deep Learning Developers often encounter challenges such as optimizing model performance for real-time inference, managing resource constraints (like GPU/CPU availability), and ensuring model reproducibility across different environments. Additionally, integrating deep learning models into existing software systems and maintaining them over time can be complex, especially as data and requirements evolve. Collaborating closely with DevOps, data engineers, and QA teams is essential to address these challenges and ensure smooth deployment and ongoing reliability.

What engineer makes $500,000 a year?

Highly experienced deep learning developers or AI engineers with specialized skills in neural networks, large-scale data processing, and advanced machine learning frameworks can earn $500,000 or more annually, especially in senior or leadership roles at major tech companies or startups. Such roles often require advanced degrees, extensive experience, and a strong track record of deploying impactful AI solutions.

What engineers make $300,000 a year?

Deep learning developers and AI engineers with extensive experience, advanced skills in machine learning frameworks, and strong domain expertise can earn $300,000 or more annually, especially in high-demand industries or senior roles. Compensation often includes base salary, bonuses, and stock options, particularly at leading tech companies or startups with significant funding.
What cities in Texas are hiring for Deep Learning Developer jobs? Cities in Texas with the most Deep Learning Developer job openings:
Deep Learning Developer jobs near you
Infographic showing various Deep Learning Developer job openings in Texas as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, 2% Contract, and 1% Nights. Highlights an 72% Physical, 2% Hybrid, and 26% Remote job distribution.
AWS Gen AI / ML Engineer

AWS Gen AI / ML Engineer

NAVA Software Solutions

Plano, TX • On-site

Full-time

Posted yesterday

Job description

NAVA Software solutions is looking for an AWS Gen AI / ML Engineer
Details:
AWS Gen AI / ML Engineer
Location: Plano, TX - Onsite 5 days
Job Type: Contract
Description: We are seeking an AWS ML Cloud Engineer to design, deploy, and optimize cloud-native machine-learning systems that power our next-generation predictive-automation platform. You will blend deep ML expertise with hands-on AWS engineering, turningdata into low-latency, high-impact insights. The ideal candidate commands statistics, coding, and DevOps-and thrives on shipping secure, cost-efficient solutions at scale
Objectives of this role
  • Design and productionize cloud ML pipelines (SageMaker, Step Functions, EKS) that advance predictive-automation roadmap
  • Integrate foundation models via Bedrock and Anthropic LLM APIs to unlock generative-AI capabilities
  • Optimize and extend existing ML libraries / frameworks for multi-region, multi-tenant workloads
  • Partner cross-functionally with data scientists, data engineers, architects, and security teams to deliver end-to-end value
  • Detect and mitigate data-distribution drift to preserve model accuracy in real-world traffic
  • Stay current on AWS, MLOps, and generative-AI innovations; drive continuous improvement

Responsibilities
  • Transform data-science prototypes into secure, highly available AWS services; choose and tune the appropriate algorithms, container images, and instance types
  • Run automated ML tests/experiments; document metrics, cost, and latency outcomes
  • Train, retrain, and monitor models with SageMaker Pipelines, Model Registry, and CloudWatch alarms
  • Build and maintain optimized data pipelines (Glue, Kinesis, Athena, Iceberg) feeding online/offline inference
  • Collaborate with product managers to refine ML objectives and success criteria; present results to executive stakeholders
  • Extend or contribute to internal ML libraries, SDKs, and infrastructure-as-code modules (CDK / Terraform)

Skills and qualifications
  • Primary technical skills
  • AWS SDK, SageMaker, Lambda, Step Functions
  • Machine-learning theory and practice (supervised / deep learning)
  • DevOps & CI/CD (Docker, GitHub Actions, Terraform/CDK)
  • Cloud security (IAM, KMS, VPC, GuardDuty)
  • Networking fundamentals
  • Java, Springboot, JavaScript/TypeScript & API design (REST, GraphQL)
  • Linux administration and scripting
  • Bedrock & Anthropic LLM integration

Secondary / tool skills
  • Advanced debugging and profiling
  • Hybrid-cloud management strategies
  • Large-scale data migration
  • Impeccable analytical and problem-solving ability; strong grasp of probability, statistics, and algorithms
  • Familiarity with modern ML frameworks (PyTorch, TensorFlow, Keras)
  • Solid understanding of data structures, modeling, and software architecture
  • Excellent time-management, organizational, and documentation skills
  • Growth mindset and passion for continuous learning

Preferred qualifications
  • 10+ years of Software Experience
  • 3+ years in an ML-engineering or cloud-ML role (AWS focus)
  • Proficient in Python (core), with working knowledge of Java or R
  • Outstanding communication and collaboration skills; able to explain complex topics to non-technical peers
  • Proven record of shipping production ML systems or contributing to OSS ML projects
  • Bachelor's (or higher) in Computer Science, Data Engineering, Mathematics, or a related field
  • AWS Certified Machine Learning - Specialty and/or AWS Solutions Architect - Associate a strong plus
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About NAVA Software Solutions

Sourced by ZipRecruiter

NAVA is a strategic partner for companies seeking to develop or customize software and products. Our team of experts leverages cutting-edge technology and deep industry knowledge to provide customized solutions that drive business success. Whether you're looking to improve your operations, increase efficiency, or bring a new product to market, NAVA has the expertise and resources to help you achieve your goals. Trust us to be your partner in software and product development.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Rocky Hill, CT, US

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