Forward Deployed Engineer (AI/Computer Vision)

Location: Lafayette, Louisiana, United States. Hybrid — onsite and remote.

Company

hirify.global delivers outsourced services and workforce solutions across North America.

What you will do

• Own technical delivery of shortlisted proof-of-concepts, including due diligence, architecture assessment, risk tracking, and progress updates.
• Scale validated PoCs into MVPs and production systems with testing, CI/CD, monitoring, security controls, and operational documentation.
• Design and execute pilots, define success criteria, gather user feedback, and create rollout, migration, integration, and knowledge-transfer plans.
• Build and maintain computer vision pipelines for large image datasets and architect cloud AI workloads for training and inference.
• Develop Python tooling for preprocessing, model training, deployment, monitoring, retraining, and continuous improvement.
• Collaborate with enterprise architecture, business, product, client, and engineering teams to translate business problems into ML solutions.

Requirements

• At least 7+ years of professional software engineering experience.
• Hands-on experience with at least one major cloud platform — AWS, Azure, or GCP — and modern DevOps practices.
• Experience with computer vision and deep learning frameworks such as PyTorch, TensorFlow, or OpenCV.
• Experience building, training, and fine-tuning image-processing and deep-learning models for classification, detection, and segmentation.
• Python experience for ML development, data processing, and automation.
• Experience running AI/ML training and inference workloads on AWS, Azure, or GCP, including services such as SageMaker, Azure ML, or Vertex AI.
• Experience processing and managing TB-scale datasets and associated data pipelines.
• Experience building and scaling production ML systems with MLOps practices including deployment, monitoring, and retraining.
• Hands-on software or platform engineering experience taking prototypes or PoCs into production, including scaling a PoC into an MVP, pilot, and broader production rollout.
• Strong full-stack or platform engineering background covering cloud architecture, APIs, data integration, and CI/CD.
• Experience working directly with enterprise architecture teams and standards and translating architectural guidance into working implementations.
• Bachelor's degree in computer science or a related field.

Nice to have

• Distributed and multi-GPU training and GPU optimization, including CUDA.
• Containerization and orchestration for ML workloads with Docker or Kubernetes.
• Large-scale data engineering tools such as Spark or Databricks.
• MLOps tools such as MLflow, Kubeflow, or SageMaker Pipelines, and predictive or forecasting models.

Culture & Benefits

• Hybrid work model with onsite and remote work in Lafayette, Louisiana.
• Direct-hire permanent full-time employment.
• Eligible employees may receive medical, dental, vision, spending-account, life-insurance, and voluntary-plan benefits.
• Eligible employees may participate in a 401(k) plan.