Veracity Group
Lead Machine Learning Engineer Computer Vision
Veracity Group, Little Rock, Arkansas, United States
About the job Lead Machine Learning Engineer Computer Vision
Responsibilities
Lead the design and development of
end-to-end computer vision systems , from data acquisition and preprocessing to model deployment and monitoring. Architect scalable
ML pipelines
for vision domain including detection, segmentation, and multimodal learning, ensuring reliability in both batch and real-time environments. Drive research and adoption of
state-of-the-art CV and ML techniques (e.g., Transformers, Vision-Language Models, diffusion models) to solve complex image understanding problems. Oversee the
collection, annotation, and augmentation
of training datasets, ensuring diversity and quality for robust model performance. Build frameworks for
model experimentation, reproducibility, and lifecycle management
(MLflow, Weights & Biases, or similar). Collaborate with data engineers to integrate ML workflows into
scalable data pipelines
and ensure smooth deployment on cloud platforms (AWS, Azure, GCP). Partner with product and business teams to
translate business needs into ML solutions , balancing research depth with delivery timelines. Establish and enforce
best practices for ML code quality, testing, version control, and CI/CD pipelines . Mentor and lead a team of ML/CV engineers, conducting code reviews, guiding experiments, and fostering a culture of technical excellence. Represent the ML team in
cross-functional discussions , contributing to long-term AI/ML strategy and roadmap. Requirements
Bachelors or master's degree in computer science , Machine Learning, Computer Vision, or related field . 5+ years of professional experience
in computer vision and machine learning engineering, with at least
2+ years in a technical leadership role . Strong expertise in
Python
and ML/CV frameworks:
PyTorch, TensorFlow, OpenCV . Proven experience with
deep learning architectures
(CNNs, RNNs, Transformers, Vision-Language Models). Hands-on experience with
segmentation, object detection, image similarity, and multimodal approaches . Experience in designing
scalable ML pipelines
with tools such as Apache Airflow, Docker, and Kubernetes. Familiarity with
cloud-based ML platforms
(AWS Sagemaker, GCP Vertex AI, Azure ML). Solid background in
model monitoring, explainability, and performance optimization . Strong leadership and communication skills, with a track record of
mentoring engineers
and managing cross-team initiatives. Nice to Have
Research experience or publications in
computer vision, multimodal AI, or generative models . Exposure to
3D vision, AR/VR, CAD/BIM, or graphics pipelines . Knowledge of
synthetic data generation, simulation environments, or reinforcement learning . Experience with
federated learning, edge AI, or on-device ML optimization .
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Responsibilities
Lead the design and development of
end-to-end computer vision systems , from data acquisition and preprocessing to model deployment and monitoring. Architect scalable
ML pipelines
for vision domain including detection, segmentation, and multimodal learning, ensuring reliability in both batch and real-time environments. Drive research and adoption of
state-of-the-art CV and ML techniques (e.g., Transformers, Vision-Language Models, diffusion models) to solve complex image understanding problems. Oversee the
collection, annotation, and augmentation
of training datasets, ensuring diversity and quality for robust model performance. Build frameworks for
model experimentation, reproducibility, and lifecycle management
(MLflow, Weights & Biases, or similar). Collaborate with data engineers to integrate ML workflows into
scalable data pipelines
and ensure smooth deployment on cloud platforms (AWS, Azure, GCP). Partner with product and business teams to
translate business needs into ML solutions , balancing research depth with delivery timelines. Establish and enforce
best practices for ML code quality, testing, version control, and CI/CD pipelines . Mentor and lead a team of ML/CV engineers, conducting code reviews, guiding experiments, and fostering a culture of technical excellence. Represent the ML team in
cross-functional discussions , contributing to long-term AI/ML strategy and roadmap. Requirements
Bachelors or master's degree in computer science , Machine Learning, Computer Vision, or related field . 5+ years of professional experience
in computer vision and machine learning engineering, with at least
2+ years in a technical leadership role . Strong expertise in
Python
and ML/CV frameworks:
PyTorch, TensorFlow, OpenCV . Proven experience with
deep learning architectures
(CNNs, RNNs, Transformers, Vision-Language Models). Hands-on experience with
segmentation, object detection, image similarity, and multimodal approaches . Experience in designing
scalable ML pipelines
with tools such as Apache Airflow, Docker, and Kubernetes. Familiarity with
cloud-based ML platforms
(AWS Sagemaker, GCP Vertex AI, Azure ML). Solid background in
model monitoring, explainability, and performance optimization . Strong leadership and communication skills, with a track record of
mentoring engineers
and managing cross-team initiatives. Nice to Have
Research experience or publications in
computer vision, multimodal AI, or generative models . Exposure to
3D vision, AR/VR, CAD/BIM, or graphics pipelines . Knowledge of
synthetic data generation, simulation environments, or reinforcement learning . Experience with
federated learning, edge AI, or on-device ML optimization .
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