The Senior Software Developer programs and configures software to meet TIAA business needs. Under moderate supervision, this job identifies and analyzes business software needs, writes code to optimize the performance and efficiency of the organization's IT platform/infrastructure and conducts testing to ensure programs are functioning properly.
Key Responsibilities and Duties
- Interprets written business requirements and technical specification documents to design and develop technical solutions that meet business needs in financial industry.
- Collaborates with IT and Business partners to design, develop, and troubleshoot end to end technical solutions.
- Performs coding to written technical specifications.
- Tests the resulting coding components in accordance with company standards and as defined in approved testing plans.
- Investigates, analyzes and documents reported defects – raising issues as appropriate.
- Analyzes run time profiles to debug errors that may exist.
- Performs maintenance programming and correction of identified defects.
- Solves a majority of defects that arise, but escalates complex issues to more senior team members.
Educational Requirements
- University (Degree) Preferred
Work Experience
- 2+ Years Required; 3+ Years Preferred
Physical Requirements
- Physical Requirements: Sedentary Work
Career Level
6IC
Position Summary: Describe below the primary purpose and function of this job
Reporting into the Lead - Data Science & ML Engineer will be responsible for :
Designing and developing machine learning systems. Possess expertise in statistics, programming, and data science, and it involves creating efficient applications solutions using AI/ML.
Implementing appropriate ML algorithms for solving business use cases to solve business problems using ML / AI or GPT, conducting experiments, and staying updated with the latest developments in the field. Work with data to create models, perform statistical analysis, and train and retrain systems to optimize performance. Contribute to advancements in artificial intelligence especially Generative AI .
Key Duties & Responsibilities: List up to 5 key duties and responsibilities, management responsibilities and time spent (if applicable)
- Share and expand the MDLC and Best Practices
- Interpret AI Policy and Framework into MLOPs Architecture and guide implementation
- Design ML data pipelines and engineering infrastructure to support enterprise machine learning systems at scale
- Develop and deploy scalable tools and services to handle machine learning training and inference
- Identify and evaluate new technologies to improve performance, maintainability, and reliability of the machine learning systems
- Support model development, with an emphasis on auditability, versioning, and data security
- Facilitate the development and deployment of proof-of-concept machine learning systems
- Design and Develop machine learning systems
- Research and implement appropriate ML algorithms and tools for business use cases.
- Develop machine learning applications according to requirements.
- Select appropriate datasets and data representation methods.
- Run machine learning tests and experiments.
- Perform statistical analysis and fine-tuning using test results.
- Train and retrain systems when necessary.
- Extend existing ML libraries and frameworks.
- Keep abreast of developments in the field.
Management/Leadership Responsibility: Is management of people a primary focus of the role? If so, how many direct and indirect employees are managed? Do any of them manage a function or process?
NA
Budget Responsibility: Does the position have responsibility for Revenue, Operating (expense) Budget, etc.? If so, what is the scope?
N/A
Impact:
NA
NA
Business or Industry Expertise: Describe the degree of knowledge and understanding required of TIAA’s business and industry, commercial environment and of competitors products and services.
Interactions / Interpersonal Skills: Describe the nature and level of interactions this job has with others, both internally and externally. Explain any specific interpersonal skills necessary to successfully perform this role (i.e., negotiation skills, represents business at external events or to governmental bodies, etc. ).
Job Requirements And Qualifications: Indicate the minimum and preferred education and experience for the job and any licenses and certifications required
Required Education:
Masters
(add “other” details here)
Preferred Education:
Masters
(add “other” details here)
Skills and Abilities:
- 2-4+ Years of relent experience in the field.
- Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer.
- Functional knowledge of the interplay between Model Governance, Change and Release Management
- Strong software engineering skills in RDMS, Sql, Pyspark etc.
- Good in Data Structures and Algorithms.
- Fluency in Python and Good with Linux scripting
- Experience working with cloud computing and database systems.
- Experience building custom integrations between cloud-based systems using APIs, real time data pipeline
- Apply Platform engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
- Knowledge of Linux OS and Scripting.
- Knowledge of Kubernetes / Open Shift and Containerization .
- Knowledge of Automation and Automation mindset.
- Should have managed Platform related activities in the past Experience.
- Experience developing and maintaining ML systems built with open source tools
- Familiarity with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc.)
- Ability to translate business needs to technical requirements
- Strong understanding of software testing, benchmarking, and continuous integration
- Exposure to machine learning methodology and best practices
A bachelor's or master's degree in computer science, data science, information science or related field, or equivalent work experience. Experience - 7- 12 Yrs
Related Skills
Application Programming Interface (API) Development/Integration, Automation, Communication, Consultative Communication, Containerization, DevOps, Enterprise Application Integration, Influence, Organizational Savviness, Problem Solving, Prototyping, Relationship Management, Scalability/Reliability, Software Development Life Cycle, Systems Design/Analysis
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Company Overview
TIAA Global Capabilities was established in 2016 with a mission to tap into a vast pool of talent, reduce risk by insourcing key platforms and processes, as well as contribute to innovation with a focus on enhancing our technology stack. TIAA Global Capabilities is focused on building a scalable and sustainable organization , with a focus on technology , operations and expanding into the shared services business space.
Working closely with our U.S. colleagues and other partners, our goal is to reduce risk, improve the efficiency of our technology and processes and develop innovative ideas to increase throughput and productivity.
We are an Equal Opportunity Employer. TIAA does not discriminate against any candidate or employee on the basis of age, race, color, national origin, sex, religion, veteran status, disability, sexual orientation, gender identity, or any other legally protected status.
Accessibility Support
TIAA offers support for those who need assistance with our online application process to provide an equal employment opportunity to all job seekers, including individuals with disabilities.
If you are a U.S. applicant and desire a reasonable accommodation to complete a job application please use one of the below options to contact our accessibility support team:
Phone: (800) 842-2755
Email: [email protected]
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