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.
Job DescriptionRESPEC 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:
Candidates with one or more of the following qualifications will receive additional consideration:
- 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
Selected candidates must successfully complete required background investigations before beginning work, including:
· 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
Please review the following carefully 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.
Skills Required
- 8+ years of professional experience
- Production-level Python development (3+ years)
- Experience deploying and managing ML workloads on cloud platforms (AWS, Azure, GCP, or OCI)
- Experience with containerization and orchestration (Docker, Kubernetes)
- DevOps/Platform engineering experience including CI/CD implementation (Azure DevOps, GitHub Actions, Jenkins or comparable)
- Experience with configuration/automation tools (Ansible)
- Experience with SQL databases (PostgreSQL, MySQL) and NoSQL and vector databases
- Bash and PowerShell scripting
- 3+ years experience with NLP, LLMs, transformer architectures, RAG, fine-tuning, and prompt engineering
- 3+ years experience in time series analytics (forecasting, anomaly detection, real-time monitoring)
- 3+ years experience building recommendation systems (collaborative filtering, ranking, personalization)
- MLOps tool experience (MLflow, Weights & Biases, Kubeflow, Apache Airflow or similar)
- Experience with distributed AI training (multi-GPU, multi-node, data parallelism)
- Computer vision experience with PyTorch, TensorFlow, OpenCV, YOLO, object detection and image segmentation
- Feature engineering and feature store experience (Feast, Tecton)
- Model optimization experience (quantization, pruning, knowledge distillation)
- Experience with alternative/open-source LLM platforms (Ollama, Hugging Face, other open-source ecosystems)
- Production AI/ML delivery: built and deployed 2-3 ML models used by real users (2+ years)
- Ability to work on-site in Austin, Texas at least 4 days per week and reliably commute
- Must be legally authorized to work in the United States for the duration of the engagement
- Background screening clearance (criminal history, state/county checks, sex offender registry) required
- GIS/spatial analysis, transportation/smart-city, Unreal Engine, digital twin, Google Maps/Cesium API, Polygonflow Dash experience
RESPEC Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about RESPEC and has not been reviewed or approved by RESPEC.
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Retirement Support — - Retirement Support: Retirement benefits are positioned as a meaningful part of total rewards through the combination of an ESOP and a 401(k). Long-term wealth-building potential is emphasized as a differentiator versus base-salary-only comparisons.
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Healthcare Strength — - Healthcare Strength: Core medical, dental, and vision coverage is presented as a standard, comprehensive foundation. Additional protection coverage (life and disability) is also included, strengthening the overall benefits stack.
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Fair & Transparent Compensation — - Fair & Transparent Compensation: Pay is characterized as generally fair-to-good when viewed across roles and in combination with total rewards. Clear salary ranges appearing in some job postings further support expectations-setting for certain positions.
RESPEC Insights
What We Do
In a world where one superhero can handle almost any problem, our entire team of award-winning technology experts is on a mission to make your business better. With extra vision to see solutions that others can’t and vast knowledge to bridge the gaps that others don’t, we’re transformers with the know-how to solve the world’s hardest problems. At RESPEC, we thrive on technology and making our clients successful. This is why we do what we do. From the depths of a cavern to the heights of a volcano, from an antiquated computer system to a business in dire need of re-engineering, our technical and business experts find solutions for extreme situations... like the time we cleansed and migrated 100 million rows of legacy data or the time we protected Mt. Rushmore. Know-How is Everything. We use our resourcefulness and vast experience to solve problems. It’s called know-how. And when you have it, problems aren’t problems at all. Know-how defines the core of who we are. It is how our clients see us. Know-how speaks to ingenuity, aptitude, and skill—it is not merely knowledge; it is knowledge on how to get things done. Imagine having access to a think tank with hundreds of diversely talented engineers, scientists, programmers, and developers under one roof—that’s RESPEC. Each team member is highly trained and skilled in understanding and applying the laws of a specific universe to solve any kind of problem. That’s why we have to talk about our team in terms of superheroes.








