Computer Vision Remote Jobs in Elgin, TX (NOW HIRING)

Big challenges need bold thinkers.

If you’re someone who sees problems as opportunities, you’ll thrive here. RESPEC is 100% employee-owned, which means we take ownership of every challenge. Here, your ideas drive real solutions. Since 1969, we’ve tackled complex challenges in energy transition, infrastructure resilience, digital transformation, and sustainability.

At RESPEC, you’ll work alongside clients to take on critical problems. Depending on your expertise, you might design infrastructure in remote locations, develop renewable energy solutions for global projects, or apply data-driven technology to improve mining and water systems.

We bring deep technical knowledge, real-world experience, and a commitment to work that matters. If you're looking for a place where your contributions have real impact, you’ll fit right in.

We do not accept unsolicited resumes from third-party recruiters.

RESPEC is seeking an experienced Software Developer Specialist to support a major transportation technology initiative for our government client in Austin, Texas. This role focuses on designing, developing, deploying, and optimizing advanced Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision, and cloud-based solutions that support large-scale operational and business objectives.

The ideal candidate will bring deep expertise across AI/ML engineering, cloud platforms, MLOps, DevOps, and production-grade software development while collaborating with technical and business stakeholders in a highly visible public-sector environment.

Responsibilities:

• Design, develop, test, and deploy scalable AI/ML solutions in cloud environments.
• Build and maintain production-grade machine learning pipelines and model deployment frameworks.
• Develop applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and transformer-based architectures.
• Create and optimize NLP solutions, recommendation systems, forecasting models, and anomaly detection systems.
• Design and implement computer vision solutions for real-time and large-scale data processing.
• Develop and maintain MLOps workflows, model monitoring, and automated retraining processes.
• Build and manage CI/CD pipelines supporting AI and software delivery.
• Containerize and deploy applications using Docker and Kubernetes.
• Collaborate with cross-functional teams to gather requirements and translate business needs into technical solutions.
• Optimize model performance through quantization, pruning, distillation, and distributed training techniques.
• Work with structured, unstructured, vector, and spatial datasets to support analytics and predictive modeling initiatives.
• Document solutions, architectures, and deployment processes according to client standards.
• Participate in technical reviews, troubleshooting, and ongoing operational support.

8+ Years of Experience Required

• Cloud Platforms & AI Infrastructure
• AWS, Microsoft Azure, Google Cloud Platform (GCP), or Oracle Cloud Infrastructure (OCI)
• Deploying and managing machine learning workloads in cloud environments
• Utilizing AI/ML services across major cloud providers
• DevOps & Platform Engineering
• Ansible
• Docker
• Kubernetes
• CI/CD implementation and automation
• Database Technologies
• SQL databases including PostgreSQL and MySQL
• NoSQL databases
• Vector databases
• Automation & Scripting
• Bash scripting
• PowerShell scripting
• CI/CD Tools
• Azure DevOps
• GitHub Actions
• Jenkins
• Comparable enterprise CI/CD platforms

3+ Years of Experience Required

• Python Development
• Production-level Python application development
• Building scalable backend and AI-driven solutions
• Natural Language Processing & Large Language Models
• Transformer architectures
• Retrieval-Augmented Generation (RAG)
• Fine-tuning models
• Prompt engineering
• LLM application development
• Time Series Analytics
• Forecasting
• Sequential modeling
• Anomaly detection
• Real-time monitoring systems
• Recommendation Systems
• Collaborative filtering
• Ranking algorithms
• Personalization engines
• Content recommendation platforms
• MLOps
• MLflow
• Weights & Biases
• Kubeflow
• Apache Airflow
• Similar MLOps platforms
• Distributed AI Training
• Multi-GPU environments
• Multi-node training
• Data parallelism
• Large-scale model training
• Computer Vision
• PyTorch
• TensorFlow
• OpenCV
• YOLO
• Object detection
• Image segmentation
• Real-time inference systems
• Feature Engineering
• Feature stores such as Feast or Tecton
• Advanced feature engineering methodologies
• Model Optimization
• Quantization
• Pruning
• Knowledge distillation
• Alternative/Open-Source LLM Platforms
• Ollama
• Hugging Face
• Other non-frontier/open-source model ecosystems

2+ Years of Experience Required

• Production AI/ML Delivery—Demonstrated experience building and deploying at least 2–3 machine learning models used by real-world users in production environments

Preferred Qualifications

• GIS and spatial data analysis experience
• Transportation, logistics, or smart-city technology experience
• Computer vision applications involving infrastructure, roadway, or vehicle-related data
• Public-sector data governance, compliance, and security experience
• Unreal Engine experience
• Digital twin implementation experience
• Google Maps Cesium API experience
• Polygonflow Dash experience

Schedule

• Monday through Friday
• 8:00 AM to 5:00 PM Central Time
• State holidays observed per client schedule

On-Site Requirement

• Minimum of 4 days per week on-site in Austin, Texas
• Remote work flexibility is limited and subject to client approval

Important

Candidates must be able to reliably commute to the Austin office throughout the engagement.

Work Authorization

Applicants must be legally authorized to work in the United States throughout the duration of the engagement.

Background Screening

• Criminal history review
• State and county-level checks
• Sex offender registry review
• Additional client-required screenings if applicable

Employment Conditions

• Overtime may occasionally be required and must receive prior client approval.
• Candidates may be asked to support occasional evening, weekend, or holiday activities based on project demands.
• Time reporting must comply with client-established procedures and systems.

Candidate Considerations Before Applying

• Relocation assistance is not specified.
• Candidates must be available to start near the anticipated project start date.
• Extended absences may impact project eligibility.
• Background screening is mandatory.
• Only candidates authorized to work in the United States will be considered.
• Compensation is subject to client-established limits and final approval.

If you are passionate about applying advanced AI, machine learning, computer vision, and cloud technologies to impactful public-sector initiatives, we encourage you to apply and join RESPEC's growing government technology practice.

All your information will be kept confidential according to EEO guidelines.