Sr. Applied AI/ML Engineer (Only w2)

• We are seeking a highly experienced and technically proficient Applied AI/ML Engineer with a strong background in capital markets surveillance to enhance and tune Behavox AI models.
• This role requires deep domain knowledge, hands-on experience with advanced AI/ML techniques, and the ability to work with large, complex datasets to improve model accuracy, reduce false positives, and ensure regulatory compliance.

Key responsibilities

• Model Enhancement and Tuning: Work directly on Behavox's proprietary LLM 2.0 and other AI risk policies to refine and improve their performance.
• Performance Optimization: Use advanced statistical analysis and machine learning techniques to further reduce alert volumes while dramatically increasing the true positive detection rate for market abuse and misconduct cases.
• Data Analysis: Work with terabytes of communications, voice, and transaction data to uncover patterns and train new features for risk detection.
• Regulatory Compliance and Auditability: Ensure all model enhancements align with regulatory requirements (e.g., FINRA, SEC) and maintain the high level of explainability and transparency required by regulatory bodies and client governance teams.
• Model Validation and Governance: Partner with internal teams to conduct rigorous model risk and governance testing, including using the Scenario Testing Lab to validate and refine new policy configurations.
• Collaboration: Work closely with the Product Management, Data Science, and Engineering teams to translate market needs and emerging threats into robust, scalable AI solutions.
• Technical Leadership: Serve as a subject matter expert on AI model behavior and tuning, providing guidance and mentorship to other engineers and data scientists.

• Required skills and qualifications
• Experience: 5+ years of hands-on experience as an Applied AI/ML Engineer or Data Scientist, with a focus on model tuning and enhancement in a production environment.
• Domain Expertise: Strong, demonstrable knowledge of capital markets, financial trading activities, and compliance surveillance regulations (e.g., market abuse, insider trading, information barriers).

Technical Skills:

• Proficiency in machine learning frameworks such as PyTorch or TensorFlow, with deep experience in training, tuning, and deploying complex models.
• Expertise in Natural Language Processing (NLP) and Large Language Models (LLMs). Experience with transformer architectures and fine-tuning models on domain-specific data is a must.
• Experience with big data technologies (e.g., Spark, Kafka) and cloud platforms (Google Cloud Platform, AWS).
• Strong programming skills in Python and SQL.

• Analytical Abilities: Exceptional problem-solving skills, with a proven ability to perform root cause analysis on model performance and translate findings into actionable improvements.
• Communication: Excellent communication skills, capable of explaining complex technical concepts to non-technical stakeholders, including compliance officers and executives.
• Education: Bachelor's or Master's degree in Computer Science, Data Science, Quantitative Finance, or a related technical field.