Avp, Global Ai Engineer

1. Working closely with business stakeholders, product managers, and data engineers to design,
develop, and deliver high performance AI/ML models including computer vision,
NLP, semantics engine, linguistics analysis, risk-management, and time-series
prediction models, etc.

2. Developing, training, tuning, and optimizing AI models and algorithms.

3. Implementing complex real-time data and AI/ML applications to capture and codify
knowledge and automate decisions.

4. Developing ML/AI models for business teams along with metrics to track their accuracy
and performance.

5. Overseeing the full lifecycle of ML model development from ideation and data exploration, algorithm design and testing, model development, tests and registrations, model versions managements, to monitoring and tuning in production.

6. Evaluating ML algorithms that could be used to solve a given problem and ranking them by their success probability.

7. Acting as an internal resource for AI/ML specific needs, providing guidance, analysis, and context to internal stakeholders during meetings and other strategy activities.
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1. Machine Learning;
• Familiar with MLFlow, Kedro, Pyspark, Pytorch frameworks (Over 5 years)
• Expertise of using commonly used ML/AI Models/libraries such as Pandas, Numpy, Tensorflow2/3, Keras, BERT, LayoutLMV1/2/3 as well as regressions, decision trees, random forest, K-means, etc traditional ML algorithms. (Over 10 years)
• Expertise of distributed ML/AI training libraries/models: Koalas, Horovod, DDP.
2. Python programing and Software Engineering
• Expertise of Pythonic clean coding, developing decorators, generators and descriptors for Python modules/libraries (over 10 years)
• Expertise of Software Design by Contract, particular over 10 years of DRY/OAOO, YAGNI, KIS, EAFP/LBYL, Defensive programming
• Expertise of separating cohension and coupling concerns in software design. (Over 10 years)
• Expertise of structing the code and orthogonality in software. (Over 10 years)
• Expertise of the SOLID Principles (Single responsibility, Open/closed, Liskov's substitution, Interface segregation and Dependency Inversion) (Over 10 years)
3.Cloud DevSecOps
• Over 5 years of coding container image dockfile and K8S
• Over 5 years of coding YAML scripts
• Expertise of building CI/CD pipelines, particular over 10 years of programming in Jenkins, Github, Nexus, Sonar, Unit test framework, Pytest.
• Over 5 years of Cloud, familiar with at least 2 of Azure, GCP and AWS.
• Familiar with node affinity, container, pods, namespace and cluster (over 5 years)
• Over 5 years of protecting data in production using Key-vaults, cloud HSM, KMS.

Requires minimal Master's degree or foreign equivalent in Computer Science, Electrical Engineering, or a closely-related field, and at least (10) years of experience of ML R&D and 5-10 years years of ML related programing as well as at least 5 years of Cloud DevSecOps experience or related occupation. Ph.D. is preferred.
The pay range for the role is $117,000 to $189,000. The specific offer will depend on an applicant's skills and other factors. This role may also be eligible to participate in a discretionary annual incentive program. Chubb offers a comprehensive benefits package, more details on which can be found on our careers website. The disclosed pay range estimate may be adjusted for the applicable geographic differential for the location in which the position is filled.

ABOUT US

Chubb is the world's largest publicly traded property and casualty insurer. With operations in 54 countries, Chubb provides commercial and personal property and casualty insurance, personal accident and supplemental health insurance, reinsurance, and life insurance to a diverse group of clients. The company is distinguished by its extensive product and service offerings, broad distribution capabilities, exceptional financial strength, underwriting excellence, superior claims handling expertise and local operations globally.

At Chubb, we are committed to equal employment opportunity and compliance with all laws and regulations pertaining to it. Our policy is to provide employment, training, compensation, promotion, and other conditions or opportunities of employment, without regard to race, color, religious creed, sex, gender, gender identity, gender expression, sexual orientation, marital status, national origin, ancestry, mental and physical disability, medical condition, genetic information, military and veteran status, age, and pregnancy or any other characteristic protected by law. Performance and qualifications are the only basis upon which we hire, assign, promote, compensate, develop and retain employees. Chubb prohibits all unlawful discrimination, harassment and retaliation against any individual who reports discrimination or harassment.