Senior Applied ML Engineer

Jobtailor; Colorado; On-site; USD 140,000 - 210,000; Full time

Job summary

Jobtailor is seeking an experienced ML engineer to develop CNN and LLM-powered models for computer vision, document extraction, and automated construction workflows. You will prototype, fine-tune, and assess NLP tasks such as classification, entity recognition, and summarization of construction data.

Build scalable ML pipelines and backend services that integrate into production-grade agents and digital platforms, driving end-to-end ML lifecycle from experimentation to deployment and monitoring.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or related field.
• 5+ years of experience designing and deploying applied ML systems at scale.
• Experience with computer vision (CNNs, object detection, segmentation) and NLP (LLMs, embeddings, transformers).
• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face).
• Experience with ML Ops platforms and deploying ML systems into production (MLflow, Kubeflow or equivalent).
• Experience with APIs, CI/CD pipelines, cloud platforms (AWS/Azure/GCP).
• Ability to clearly communicate technical concepts to engineers and non-technical stakeholders.
• Experience in construction, CAD/BIM, architecture, or digital twin platforms is preferred.

Responsibilities

• Develop and optimize CNN and LLM-powered models for computer vision and NLP tasks.
• Prototype, fine-tune, and assess models for classification, entity recognition, and summarization of construction data.
• Build scalable ML pipelines and backend services integrating into production-grade agents.
• Drive end-to-end ML lifecycle from experimentation to deployment and monitoring.
• Integrate retrieval, ML, and rules-based methods for reliable, explainable features.
• Collaborate with product managers, software engineers, and construction domain experts to deliver measurable business impact.

Skills

CNNs

LLMs

Object detection

Segmentation

NLP

Embeddings

Transformers

Python

PyTorch

TensorFlow

Hugging Face

MLflow

Kubeflow

AWS

Azure

GCP

Education

Bachelor’s or Master’s in CS/ML

Tools

MLflow

Kubeflow

PyTorch

TensorFlow

Hugging Face

Job description

• Develop and optimize CNN and LLM-powered models for computer vision, document extraction, and automated construction workflows.
• Prototype, fine-tune, and assess models for NLP tasks such as classification, entity recognition, and summarization of construction data.
• Build scalable ML pipelines and backend services that integrate into production-grade agents and digital platforms.
• Drive the end-to-end ML lifecycle: from experimentation and training, to deployment, monitoring, and continuous improvement.
• Integrate retrieval, ML, and rules-based methods to deliver reliable, explainable, and supportable features.
• Collaborate closely with product managers, software engineers, and construction domain experts to solve real-world challenges with measurable business impact.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or related field.
• 5+ years of experience designing and deploying applied ML systems at scale.
• Experience with computer vision (CNNs, object detection, segmentation) and natural language processing (LLMs, embeddings, transformers).
• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face).
• Experience with ML Ops platforms and deploying ML systems into production (MLflow, Kubeflow or equivalent).
• Experience with APIs, CI/CD pipelines, cloud platforms (AWS/Azure/GCP).
• Ability to clearly communicate technical concepts to both engineers and non-technical stakeholders.
• Experience applying ML in construction, CAD/BIM, architecture, or digital twin platforms is preferred.
• Familiarity with graph-based retrieval, RAG pipelines, or multimodal ML is preferred.

Core Competencies

Demonstrates expertise in developing and optimizing CNN and LLM-powered models for computer vision and NLP tasks, with a strong focus on building scalable ML pipelines and deploying production-grade systems. Proficient in collaborating with cross-functional teams to deliver impactful solutions in the construction domain.

Highest-signal resume keywords

• Computer Vision (CNNs, Object Detection, Segmentation)
• Natural Language Processing (LLMs, Embeddings, Transformers)
• Python Programming
• ML Frameworks (PyTorch, TensorFlow, Hugging Face)
• ML Ops Platforms (MLflow, Kubeflow)

ATS Optimization Keywords

Hard Skills

• Machine Learning
• Model Deployment
• Data Classification
• Entity Recognition
• Model Fine-Tuning
• Scalable ML Pipelines
• Continuous Improvement
• APIs
• CI/CD Pipelines
• Cloud Platforms (AWS/Azure/GCP)

Soft Skills

• Clear Communication
• Collaboration

Certifications & Qualifications

• Bachelor’s or Master’s Degree in Computer Science, Machine Learning, or Related Field

Industry Keywords

• Construction
• CAD/BIM
• Architecture
• Digital Twin Platforms
• Graph-Based Retrieval
• RAG Pipelines
• Multimodal ML