AI Solutions Engineer Job New Haven area,Connecticut USA,IT/Tech

Design, develop, and implement robust data pipelines for collecting, cleaning, and preparing data for model training and evaluation, specifically from web and API traffic, and security event logs.
Select appropriate machine learning models, with a particular emphasis on smaller, efficient models suitable for security applications (e.g., WAF, bot detection, anomaly detection, API threat prevention) and other performance-critical use cases.
Train, fine-tune, and evaluate machine learning models, employing techniques to optimize for performance, cost, and accuracy in identifying and mitigating security threats.
Deploy models into production environments, establishing and managing MLOps processes for continuous integration, delivery, and training (CI/CD/CT) within our cloud security infrastructure.
Monitor model performance in production, implementing strategies for regular re-tuning and updates to ensure continued accuracy and relevance against evolving threat landscapes.
Collaborate with product management and engineering teams to understand requirements, define AI solutions, and integrate them into existing products and new features for web and API security.
Drive the evolution of our MLOps practices to enhance the speed, reliability, and scalability of our AI deployments, fostering a culture of continuous improvement and innovation in AI operations.
Stay up-to-date with the latest advancements in applied AI, MLOps, and relevant technologies, particularly in cybersecurity AI, threat intelligence, and Generative AI for security.
Document AI solutions, processes, and model performance for internal stakeholders.

Job Description:

3-5 years of hands-on experience in applied AI or machine learning engineering, preferably in a cybersecurity context.
Proven experience in developing, deploying, and maintaining machine learning models in production environments for security use cases.
Strong proficiency in Python and relevant AI/ML libraries/frameworks (e.g., Scikit-learn, Tensor Flow Lite, PyTorch, ONNX, Hugging Face Transformers, MLflow, Kubeflow).
Hands-on experience with data cleaning, feature engineering, model selection, and hyperparameter tuning, particularly for smaller, efficient models tailored to security data.
Demonstrable experience in building and maintaining robust data pipelines and CI/CD/CT for ML systems.
Software development experience in building high-performant, secure, and scalable web applications or security services.
Fair understanding of dynamically scalable cloud architectures, ideally AWS.
Excellent problem-solving and analytical skills.
Strong verbal and written communication skills.
Collaborative, quality-conscious, and self-motivated with a proactive approach.
A passion for building, deploying, and meticulously managing the full lifecycle of impactful AI systems.
Experience with security AI use cases like anomaly detection, threat intelligence, or user behaviour analytics.
Experience with Layer 7 security concepts, web application firewalls (WAF), API security, and bot mitigation techniques.

#J-18808-Ljbffr


Increase/decrease your Search Radius (miles)



Job Posting Language