Lead Machine Learning Engineer- Data
Lead Machine Learning Engineer- Data
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1 Vacancy
Job Description
The Data and Artificial Intelligence Platform group is a key component of Visas Technology organization providing the enabling technology and processes to handle Visas data assets and deliver valuable information products and services to customers. Our team delivers secure highquality and easytouse Visa core data assets along with reliable and scalable data platforms. Our platform operationalizes the delivery of AI and decision intelligence to ensure ongoing business value to Visa and our clients.
As a Lead Machine Learning Engineer Data with expertise in Machine Learning and Data Engineering you will drive innovation in developing purposefit data solutions using cuttingedge technologies. You will be responsible for executing a data strategy that leverages our data assets to drive innovation through data engineering and GenAI solutions including developing a synthetic data engine. You will also guide and mentor junior engineers ensuring security scalability performance and reliability in all data solutions. As an individual contributor based in Foster City California USA you will be reporting to Sr. Director of Data as a Service (DaaS) team. This team is growing fast! Join us and be an integral part of the group that is at the leading edge of pioneering Data and AI.
What We Offer:
Exciting Challenges: We work at a scale rarely seen in the industry solving complex data and AI problems across the entire stack offering limitless opportunities to leverage and lead in this evergrowing field.
Teamwork and Fun: Each of us brings diverse and rich experiences to the team enabling us to deliver much more than the sum of our parts and have fun at the same time.
Fantastic People: With strong leadership you will have the opportunity to learn collaborate and deliver together with some of the best and most creative minds in the industry.
About the Role:
Lead the design and architecture of robust scalable data engineering platforms and infrastructure including data pipelines data warehouses and data lakes (onprem and cloudbased).
Oversee the entire data lifecycle from data acquisition and ingestion to transformation storage and analysis.
Develop a synthetic data engine to generate ondemand privacy enhanced synthetic data where actual production data cannot be used ensuring scalability and compliance.
Build and experiment with modeling and scoring algorithms including custom algorithms and packaged tools based on machine learning analytics and statistical techniques.
Champion the adoption of GenAI and Agentic AI technologies and develop strategies to integrate them into existing workflows or build new ones.
Ensure data security privacy governance and compliance with all relevant regulations and develop and implement auditable policies and procedures.
Lead and guide a highperforming data engineering and ML team fostering a culture of innovation and continuous learning.
Partner with business stakeholders to understand their needs and translate them into actionable datadriven solutions.
Stay uptodate on emerging data and AI trends and technologies.
This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.
Qualifications :
Basic Qualifications:
- 10 or more years of work experience with a Bachelors Degree or at least 8 years of work experience with an Advanced Degree (e.g. Masters/ MBA/JD/MD) or at least 3 years of work experience with a PhD.
Preferred Qualifications:
- 12 or more years of work experience with a Bachelors Degree or 810 years of experience with an Advanced Degree (e.g. Masters MBA JD MD) or 6 years of work experience with a PhD.
- Expertise in leadingedge areas such as Machine Learning Deep Learning Stream Computing and MLOps.
- Expertise with GenAI technologies (e.g. Large Language Models NLP) and RAGbased architecture and vector databases.
- Strong proficiency in programming languages like Java Scala SQL and REST.
- Any experience with Machine Learning Model Deployment/Development and/or Predictive Modeling is highly preferred.
- Experience with Prometheus Grafana Docker or Kubernetes is highly preferred.
- 12 years of handson experience and a proven track record of building and deploying complex data pipelines and architectures using the latest technologies.
- Expertise in onprem and cloudbased data platforms (AWS Azure) and related data storage and processing tools (e.g. Databricks S3.
- Relevant exposure to modeling techniques such as logistic regression SVM decision trees or neural networks.
Additional Information :
Work Hours: Varies upon the needs of the department.
Travel Requirements: This position requires travel 510 of the time.
Mental/Physical Requirements: This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk communicate in person and by telephone frequently operate standard office equipment such as telephones and computers.
Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race color religion sex national origin sexual orientation gender identity disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.
Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law including the requirements of Article 49 of the San Francisco Police Code.
U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is $194600 to $282150 per year which may include potential sales incentive payments (if applicable). Salary may vary depending on jobrelated factors which may include knowledge skills experience and location. In addition this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical Dental Vision 401 (k) FSA/HSA Life Insurance Paid Time Off and Wellness Program.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
