Machine Learning Engineer II

ConstructConnect•Atlanta, GA

2d•Hybrid

About The Position

This position is hybrid in Peachtree Corners, Georgia and sits within our Product Development division, which develops, tests, and improves our software solutions in an innovative and collaborative environment. ConstructConnect is looking for a full-time Machine Learning Engineer II. The construction industry is ready for innovation. Metrics show an increase in buildings but a downturn in available labor. ConstructConnect is ready to fill this gap through a variety of artificial intelligence and machine learning approaches. Our opportunity to achieve this goal is vast and varied. We are leveraging generative AI, computer vision and natural language processing to name a few. The ideal candidate for this role will have a passion for AI and ML, with a strong background in Python and experience building and deploying machine learning solutions. They will bring an energy for innovation and a desire to learn new techniques and tools. Come help us build the future of the pre-bid construction industry!

Requirements

Proficiency in machine learning frameworks, such as TensorFlow, PyTorch, or scikit-learn.
Strong programming skills in Python, with experience in data manipulation, analysis, and visualization using libraries such as Pandas, NumPy, and Matplotlib.
Experience with cloud platforms, such as GCP, and deploying models to production environments.
Proficiency with CI/CD pipelines to automate testing, building, and deploying ML models.
Experience with container technologies such as Docker, Kubernetes etc.
Proficiency in using version control systems like Git for tracking changes in ML code and models.
Experience with MLOps tools such as Kubeflow, TFX, or others to streamline the ML lifecycle.
Familiarity with Terraform to streamline infrastructure provisioning and deployment processes.
Expertise with computer vision libraries and tools, such as OpenCV, scikit-image.
Effective communication skills and experience distilling and presenting complex quantitative analysis into action-oriented
Understanding of Generative AI and deep learning architectures for computer vision and NLP.
Knowledge of computer vision techniques, such as classification, object detection, and image segmentation.
Agile development mindset, appreciating the benefit of constant iteration and improvement.
Bachelor's degree or equivalent experience in data science, Statistics, Computer Science, or a related field.

Responsibilities

Understand business objectives and develop models that help achieve them, along with metrics to track their progress
Work closely with Data scientists to build their models into production ready versions with good code practices.
Design, develop, and deploy end-to-end ML pipelines to support various AI/ML initiatives.
Design and manage scalable cloud-based infrastructures to support machine learning workflows, emphasizing data security and compliance.
Optimize and fine-tune deep learning models to improve its performance, accuracy, and efficiency.
Conduct thorough evaluations and assessments of models, providing recommendations for enhancements.
Continuously monitor, evaluate, and optimize the performance, accuracy, and cost of ML models in production cloud environments.
Contribute to the development of internal frameworks, and libraries to streamline ML
Troubleshoot and solve issues related to model deployment, scalability, and performance.
Stay informed about industry trends, best practices, and emerging technologies in AI.
Team player with the ability to balance multiple simultaneous projects.
Mentor and guide junior ML engineers.
Conducting thorough code reviews to ensure code quality and adherence to best practices.
Participate in the recruiting and onboarding of new team members.
This job description in no way implies that the duties listed here are the only ones that team members can be required to perform.