Position Overview

Job Title: Applied Research Engineer

Location: India

Department: Technology

Reporting To: Head of Research

Tookitaki is seeking an Applied Research Engineer with 6+ years of experience to lead cutting-edge AI and machine learning research in regulatory compliance and financial crime detection. This role will focus on developing innovative AI models, optimizing algorithms, and translating research into real-world applications. The ideal candidate will have a strong foundation in machine learning, deep learning, and data science, along with experience in deploying research-driven solutions at scale.

Position Purpose

The Applied Research Engineer will play a pivotal role in advancing Tookitaki's AI-driven compliance solutions by developing novel AI/ML algorithms and ensuring their practical implementation. This role bridges the gap between research and production, focusing on algorithm development, experimentation, and optimization to enhance Tookitaki's capabilities in fraud detection, risk management, and anomaly detection. The role also involves collaborating with data scientists, engineers, and regulatory teams to create cutting-edge, regulatory-compliant AI solutions.

Key Responsibilities

1.AI/ML Model Research & Development

Research, design, and implement state-of-the-art AI/ML models for fraud detection, risk assessment, and financial crime prevention.
Optimize models for accuracy, efficiency, and scalability across various financial datasets.
Experiment with graph-based AI, deep learning, and unsupervised learning techniques to improve detection capabilities.

2.Algorithm Optimization & Innovation

Develop new feature engineering and model selection techniques to enhance AI model performance.
Optimize model inference speed for real-time and batch processing scenarios.
Explore federated learning and privacy-preserving AI techniques to ensure data security and compliance.

3.Deployment & Engineering Collaboration

Work closely with ML engineers and software developers to deploy AI models into production.
Implement scalable AI pipelines that can handle large-scale financial data processing.
Ensure AI solutions are explainable, interpretable, and aligned with regulatory requirements.

4.Data Analysis & Feature Engineering

Analyze structured and unstructured financial datasets to extract meaningful features for ML models.
Design and build robust data preprocessing pipelines to enhance model accuracy and generalization.
Work with data engineering teams to ensure efficient and scalable data ingestion.

5.AI Ethics & Compliance

Develop transparent and explainable AI models to meet financial industry compliance standards.
Ensure AI models adhere to ethical AI guidelines, fairness, and bias mitigation strategies.
Collaborate with legal and compliance teams to align AI research with evolving regulatory frameworks.

Qualifications and Skills

Education

Master's or Ph.D. in Computer Science, Machine Learning, AI, Data Science, or related field.
Strong research background in AI/ML, deep learning, or statistical modeling.

Experience

6+ years of experience in applied AI research, machine learning, or data science.
Proven track record in developing and deploying AI/ML models in real-world applications.
Experience working with financial datasets, fraud detection, or regulatory compliance AI models (preferred).

Technical Expertise

Strong programming skills in Python, TensorFlow, PyTorch, or JAX.
Hands-on experience in NLP, anomaly detection, graph-based AI, and time-series analysis.
Experience with big data processing frameworks (Spark, Hadoop) and cloud AI platforms (AWS/GCP).
Expertise in model evaluation, hyperparameter tuning, and performance optimization.
Knowledge of explainable AI (XAI), adversarial learning, and bias mitigation.

Soft Skills

Strong problem-solving skills and the ability to translate complex research into practical applications.
Excellent collaboration and communication skills to work with cross-functional teams.
Ability to balance research innovation with real-world constraints and scalability.
Strong analytical mindset with a passion for continuous learning and innovation.

Key Competencies

AI/ML Research & Development: Ability to research, prototype, and implement cutting-edge AI models.
Algorithm Optimization: Expertise in fine-tuning models for real-world applications and performance improvements.
Scalability & Deployment: Hands-on experience in deploying ML models at scale.
Regulatory & Compliance Awareness: Understanding of AI ethics, explainability, and financial regulations.
Cross-Team Collaboration: Works closely with engineering, product, and compliance teams to drive AI innovation.

Success Metrics

Successfully develop and deploy at least two AI models per year to enhance Tookitaki's compliance solutions.
Improve model accuracy and efficiency by 20% through research-driven optimizations.
Ensure seamless deployment of AI models into production with 99.9% uptime.
Reduce false positives in financial fraud detection by 25%, improving risk assessment accuracy.
Publish at least one research paper or internal technical report annually on AI advancements.

Benefits

Competitive Salary: Aligned with industry standards and experience.
Professional Development: Access to training in big data, cloud computing, and data integration tools.
Comprehensive Benefits: Health insurance and flexible working options.
Growth Opportunities: Career progression within Tookitaki's rapidly expanding Services Delivery team.

Introducing Tookitaki

Tookitaki: The Trust Layer for Financial Services

Tookitaki is transforming financial services by building a robust trust layer that focuses on two crucial pillars: preventing fraud to build consumer trust and combating money laundering to secure institutional trust. Our trust layer leverages collaborative intelligence and a federated AI approach, delivering powerful, AI-driven solutions for real-time fraud detection and AML (Anti-Money Laundering) compliance.

How We Build Trust: Our Unique Value Propositions

AFC Ecosystem Community-Driven Financial Crime Protection
The Anti-Financial Crime (AFC) Ecosystem is a community-driven platform that continuously updates financial crime patterns with real-time intelligence from industry experts. This enables our clients to stay ahead of the latest money laundering and fraud tactics. Leading digital banks and payment platforms rely on Tookitaki to protect them against evolving financial crime threats. By joining this ecosystem, institutions benefit from the collective intelligence of top industry players, ensuring robust protection.
FinCense End-to-End Compliance Platform
Our FinCense platform is a comprehensive compliance solution that covers all aspects of AML and fraud preventionfrom name screening and customer due diligence (CDD) to transaction monitoring and fraud detection. This ensures financial institutions not only meet regulatory requirements but also mitigate risks of non-compliance, providing the peace of mind they need as they scale.

Industry Recognition and Global Impact

Tookitaki's innovative approach has been recognized by some of the leading financial entities in Asia. We have also earned accolades from key industry bodies such as FATF and received prestigious awards like the World Economic Forum Technology Pioneer, Forbes Asia 100 to Watch, and Chartis RiskTech100.

Serving some of the world's most prominent banks and fintech companies, Tookitaki is continuously redefining the standards of financial crime detection and prevention, creating a safer and more trustworthy financial ecosystem for everyone.

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