Senior AI/ML Engineer

Senior Level Position

🚀Position Overview

Join Multisector Hubs as a Senior AI/ML Engineer and be at the forefront of revolutionizing corporate governance through cutting-edge artificial intelligence. You’ll develop and optimize sophisticated machine learning models that power our innovative governance solutions, helping businesses navigate complex regulatory landscapes with unprecedented efficiency and accuracy.

What You’ll Work On
📄 Document analysis and intelligent processing systems.
🔮 Compliance prediction and risk assessment models.
⚡ Automated decision-making systems for regulatory compliance.
🎯 Next-generation AI applications for corporate governance .

⚙️Key Responsibilities

Model Development & Optimization
Design, develop, and optimize machine learning models for document analysis, compliance prediction, and automated decision-making systems.

Research & Innovation
Stay at the forefront of AI/ML research and implement cutting-edge techniques to solve complex corporate governance challenges.

Data Pipeline Architecture
Build robust data pipelines and infrastructure to support large-scale ML model training and inference.

Cross-functional Collaboration
Work closely with product managers, engineers, and domain experts to translate business requirements into technical solutions.

Technical Leadership
Mentor junior team members and provide technical guidance on ML best practices and architectural decisions.

Performance Monitoring
Implement monitoring systems to track model performance, detect drift, and ensure continuous improvement of AI systems.

🎯Key Impact Areas

📊 Business Intelligence
Transform raw regulatory data into actionable insights that drive strategic business decisions and improve compliance outcomes.

🛡️ Risk Mitigation
Develop predictive models that identify potential compliance risks before they become critical issues, saving millions in potential penalties.

Process Automation
Create intelligent automation systems that reduce manual compliance work by 80% while improving accuracy and consistency.

🔍 Document Intelligence
Build advanced NLP systems that can understand and extract critical information from complex regulatory documents and contracts.

📈 Scalable Solutions
Design ML architectures that can scale from startup clients to enterprise-level organizations with millions of documents.

🌟 Innovation Leadership
Pioneer new AI applications in the RegTech space and establish Multisector Hubs as a thought leader in the industry.

🎓Requirements

Essential Qualifications
Master’s or PhD in Computer Science, Machine Learning, or related field.
5+ years of experience in ML/AI development and deployment.
Expert proficiency in Python, TensorFlow/PyTorch, and scikit-learn.
Strong experience with NLP, computer vision, and deep learning.
Experience with cloud platforms (AWS, GCP, or Azure).
Proven track record of deploying ML models in production.
Preferred Qualifications
Experience in regulatory technology (RegTech) or compliance.
Knowledge of corporate governance and regulatory frameworks.
Experience with MLOps and model lifecycle management
Startup experience and ability to work in fast-paced environments.
Publications in top-tier ML/AI conferences or journals.
Experience with distributed computing and big data technologies.

🔄Application Process

Application Review: Our team reviews your application, resume, and portfolio. We look for relevant experience and passion for AI/ML innovation.
Initial Screening Call: 30-minute conversation with our HR team to discuss your background, motivations, and answer any questions about the role.
Technical Assessment: Take-home project focused on a real-world ML problem similar to what you’d work on. Showcase your problem-solving approach and technical skills.
Technical Deep Dive: 90-minute session with our senior engineers to discuss your technical assessment, dive deep into ML concepts, and explore system design.
Leadership & Culture Fit: Meet with our leadership team to discuss vision alignment, leadership style, and how you’d contribute to our startup culture.
Timeline: 60 minutes
Final Decision & Offer: We’ll make our final decision and extend an offer with competitive compensation, equity, and benefits package.

🚀Onboarding Journey

First 30 Days
Welcome & Setup: Complete IT setup, security training, and meet your team members.
Domain Deep Dive: Learn about corporate governance, regulatory landscape, and our product suite.
Codebase Exploration: Get familiar with our ML infrastructure, data pipelines, and existing models.
First Project Assignment: Start with a well-scoped project to make your first meaningful contribution.
First 90 Days
Project Ownership
Take full ownership of a key ML component or feature
Cross-team Collaboration
Work closely with product, engineering, and business teams.
Technical Leadership
Begin mentoring junior team members and contributing to technical decisions.
Performance Review
Comprehensive review with feedback and goal setting for the next quarter.

🌟 Ongoing Development & Support
📚 Continuous Learning

• $3,000 annual learning & development budget
• Conference attendance and industry events
• Internal tech talks and knowledge sharing
• Certification support (AWS, Azure, etc.)

🎯 Career Growth

• Quarterly performance reviews and goal setting
• Clear promotion pathways and criteria
• Leadership development opportunities
• Cross-functional project assignments

Apply for the Senior AI/ML Engineer

1. Personal Information
First Name
Last Name
Email
Phone Nuber
URL LinkedIn Profile
Current Location
2. Education & Certifications
Highest Degree
University/Institution
Field of Study
Relevant Certifications
3. Professional Experience
Years of AI/ML Experience
Current/Most Recent Company
Current/Most Recent Position
Key Achievements & Projects
Technical Skills & Tools
4. Position-Specific Questions
Document Analysis & NLP Experience
Compliance & Regulatory Technology Experience
Model Deployment & Production Experience
Startup Environment Experience
5. Motivation & Cultural Fit
Why are you interested in this role?
Innovation & Problem-Solving Approach
Work Style Preferences






6. Availability
Preferred Start Date
Salary Expectations
Additional Information
Documents
URL Link to your CV/Resume
URL Link to Cover Letter
URL Portfolio/GitHub 
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