IT Infrastructure Solutions Specialist

Company Description

Project Brains is a platform revolutionizing the Future of Work by connecting businesses with a community of highly skilled fractional specialists. Our goal is to help ambitious organizations achieve their growth objectives by matching business needs with experts who deliver impactful outcomes.

Today we are working with a Global Tech Consultant driving innovation in Computer Vision and Machine Learning in industrial and retail domain.

Role Description

This is a contract hybrid role for an IT Infra Solutions Specialist focussed on ML Ops. This role in based in Dallas, TX. The ML Ops Specialist will be responsible for developing, deploying, and maintaining machine learning workflows and infrastructure. Day-to-day tasks include collaboration with cross-functional teams, ensuring efficient and scalable operations, monitoring performance, managing deployments, and contributing to continuous improvement efforts. The role also involves troubleshooting issues, optimizing ML pipelines, and ensuring data security and compliance.

It will be an ideal fit for a specialist with computer vision project experience (e.g. object detection, video and image processing, metadata management and related services). Knowledge of data modelling for querying of unstructured data will be key. Experience with Big Query, PostgreSQL, Dataops, MLOps, CI​/​CD Pipeline in GCP Cloud is important, as is knowledge of Airflow, Mlflow, Git, Nvidia deepstream or other computer vision technologies.

Qualifications

Strong foundation in Analytical Skills, particularly in data processing, modeling, and optimization

Effective Communication abilities to convey complex technical information clearly to both technical and non-technical stakeholders

Experience in Operations Management and Project Management for maintaining and improving machine learning workflows

Knowledge of Sales processes and how to align ML solutions to support business development

Proficiency in working with modern ML tools, cloud platforms, and deploying scalable pipelines

A degree in Computer Science, Data Science, Machine Learning, or a related field is a must

Experience integrating machine learning solutions into business processes

Please note

Computer Vision experience is mandatory, i.e. 2+ years hands-on experience with real-time Computer Vision pipelines (YOLO, Faster-RCNN, SSD, RetinaNet).

Strong experience with video analytics, frame processing, multi-camera pipelines, and CV performance metrics (mAP, IoU, FPS, latency).

NVIDIA DeepStream ​/​ GPU Acceleration is also mandatory

Hands-on experience with NVIDIA DeepStream for GPU-accelerated CV pipelines.

Experience with TensorRT, CUDA, and optimizing models for GPU inference (T4 ​/​ L4 ​/​ A100).

Video Data Engineering experience handling unstructured data at scale (video, image) including metadata design, storage optimization, and BigQuery-based modeling.

Experience with streaming architectures (Kafka, GStreamer, RTSP ingestion).

GCP for CV is key, e.g. strong hands-on experience deploying CV workloads on GCP (GKE, Vertex AI, Dataflow, BigQuery).

Experience with GCP GPU instances and autoscaling CV workloads.

Retail Computer Vision is preferred, i.e. experience developing CV solutions for retail scenarios (shelf detection, product tracking, store analytics, queue detection, LP​/​camera systems).

MLOps Leadership for CV is important, i.e. experience leading MLOps architecture for computer vision models (CI​/​CD, rollout strategies, monitoring, drift detection).

Experience building observability dashboards for CV systems (Prometheus​/​Grafana, GPU metrics, dropped frames, throughput).

Clarifier (to avoid NLP​/​LLM-only skills)

• This role is focused on Computer Vision — NOT LLM, NLP, or text-based ML pipelines.