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Machine Learning Engineer – Data Classification & Compliance

Machine Learning Engineer – Data Classification & Compliance

IBM

8 - 13 years

5 - 9 Lacs

bengaluru

Posted:-1 days ago| Platform:

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Skills Required

compliance matlab front end kubernetes python natural language processing machine learning javascript nosql sql microservices docker pandas tensorflow java postgresql data science cassandra pytorch mongodb informatica

Work Mode

Work from Office

Job Type

Full Time

Job Description

ML Solution Design & Deployment: Design, build, train, and deploy machine learning models specifically for automated data classification across diverse data stores (SQL, NoSQL, data lakes).

Financial Services Data Expertise: Apply a deep understanding of financial data types (e.g., PII, account numbers, transaction data) to tune models for accuracy and relevance within the industry context.

Regulatory Compliance Implementation: Ensure ML models and classification rules adhere strictly to stringent regulatory standards across multiple industries (e.g., GDPR, CCPA, PCI-DSS, SOX, Basel Accords).

Containerized ML Operations: Utilize modern MLOps practices, deploying and managing machine learning models within containerized environments (Docker) for scalability and reproducibility.

Technology Stack Proficiency: Primarily develop using Python ML frameworks, while leveraging expertise in Java and JavaScript for integration with existing enterprise systems and front-end classification interfaces.

Tooling & Frameworks: Utilize expertise in various machine learning frameworks and data science platforms.

Methodology & Rules: Implement robust data classification methods, leveraging both statistical ML approaches and expert-defined business rules for high-precision results

The ideal candidate would have a strong technical aptitude and a flair for picking up new skills

The role provides ample opportunity for learning and career growth and is only constrained by the individual’s appetite for learning

Required education

Bachelor''s Degree

Preferred education

Master''s Degree

Required technical and professional expertise

8+ years of IT experience

ML Expertise: Proven experience as a Machine Learning Engineer with a strong portfolio of deployed ML solutions, particularly those involving natural language processing or data categorization.

Python Mastery: Expert-level proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas) for building sophisticated classification models.

Database Fluency: Hands-on experience working with data housed in both relational databases (e.g., PostgreSQL, Oracle, DB2) and non-relational databases (e.g., MongoDB, Cassandra).

Financial Services Data: In-depth knowledge of data structures, governance needs, and sensitive information types prevalent in the financial services sector.

Regulatory Knowledge: Strong understanding of global data privacy and compliance regulations applicable to data management.

Containerization: Practical experience with Docker and/or Kubernetes for deploying scalable microservices and ML models.

Preferred technical and professional experience

Diverse Tooling Experience: Familiarity with a range of data science and analytics platforms, such as MATLAB, Altair RapidMiner, or IBM SPSS Statistics.

Java & JavaScript Experience: Proficiency in Java for backend integration and/or JavaScript for front-end interface development related to data governance platforms is highly desirable.

Data Governance Tools: Familiarity with broader data governance and catalog tools (e.g., Informatica, Alation) and how ML integrates with these platforms.

Certifications: Relevant certifications in Machine Learning or Data Governance are a plus.

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Machine Learning Engineer – Data Classification & Compliance