AI/ML Risk Consultant
3 weeks ago
Job Role: AI/ML Risk Consultant
Availability: Immediate is preferred
Job Location: Bangalore/Mumbai
Job Purpose: -
We are seeking a professional with over 4 years of experience, specializing in machine learning, natural
language processing, and generative AI. The candidate should possess a robust background in AI/ML
model development/validation, optimization, and risk management, with a proven track record of
integrating AI/ML solutions into business strategies and managing complex regulatory and ethical
considerations.
Key responsibilities include -
∙Design, develop, train, fine-tune, evaluate, validate, and optimize ML models for enhanced
performance, accuracy, generalization, and scalability.
∙Apply strategic thinking to integrate AI solutions into existing systems and applications,
leveraging technical expertise in AI and ML.
∙Manage data risk, information security, operations, privacy, and compliance, drawing on a strong
background in risk management and governance.
∙Navigate the complexities of financial services regulations, AI standards, and ethical principles
related to AI, with a focus on managing the heightened risks of Gen AI and emerging
technologies.
∙Conduct comprehensive risk assessments for a variety of AI and Gen AI use cases, considering the
entire lifecycle from development to deployment.
∙Design and implement rigorous testing frameworks to evaluate the performance, quality, and
reliability of generative AI models.
∙Prepare and present detailed reports on AI risk metrics, including Key Control Indicators, Key
Risk Indicators, and Key Performance Indicators, to facilitate early detection of potential risks.
∙Oversee the continuous monitoring and evaluation of AI risks, adapting strategies to manage
emerging threats effectively.
∙Communicate effectively with leadership and cross-functional teams to influence outcomes and
drive results in risk management initiatives.
Skill Set Required -
∙Demonstrated practical experience in machine learning techniques, supervised, unsupervised, and
semi-supervised.
∙Experience in natural language processing (NLP), generative AI and its applications.
∙Experience with machine learning optimization and a variety of generative AI models and
techniques.
∙Strong understanding of and experience with various AI/ML model validation techniques,
including statistical tests, ablation studies, and adversarial testing. Familiarity with common
metrics and benchmarks used in the validation of generative models.
∙Knowledge of deep learning models such as GANs, diffusion models, and transformers.
∙Relevant experience in Financial Services industry would be desirable.
∙Experience in a modeller role in the financial services industry is preferred.
Education:
A degree in Engineering, MS, or PhD in relevant fields such as Statistics, Applied Mathematics, Computer
Science, or Econometrics.
Software/Tools:
∙Proficient in programming languages such as Python, R, and C++ for AI and ML model
development.
∙Skilled in using AI and ML libraries and frameworks, including TensorFlow, Keras, PyTorch, and
Scikit-learn.
∙Experience with cloud computing platforms like AWS, Azure, and GCP for deploying scalable
machine learning models would be a plus.
∙Familiar with big data technologies and distributed computing frameworks, such as Hadoop and
Spark, for handling large datasets.
∙Knowledgeable in version control systems like Git for code management and collaboration.
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