Viji Vennelakanti, Project Manager in Alpharetta, GA, United States
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Viji Vennelakanti

Verified Expert  in Project Management

Project Manager

Alpharetta, GA, United States
Toptal Member Since
July 5, 2018

Viji has 20+ years of experience in IT project management, executive leadership, and, most recently, AI and deep learning. This combined expertise makes her an invaluable asset for companies looking to build innovative products in the AI and ML sectors. Viji has served as the VP of Engineering for a US-based startup, as an IT director overseeing a team of 100+ at a US-based global nonprofit, as CTO and co-founder of an Indian fintech startup, and as a deep learning mentor on Coursera.

Project Highlights

Computer Vision Project
Served as the technical agile project manager for a computer vision startup in stealth mode that has teams in three continents. Several pilot projects were completed and resulted in successful fundraising.
Object Detection Using Computer Vision for Medical Images
Completed a POC to democratize healthcare using computer vision, a crucial step toward scaling and fundraising for a global solution.
Computer Vision for Water Meter Images
Planned and executed a project using computer vision and deep learning to "read" water meter images and determine the reading with an accuracy of 85%.


Work Experience

Consultant | Machine Learning and Project Management

2015 - PRESENT
Toptal Clients
  • Acted as the VP of Product and Engineering for a US-based startup building a web app with NLP, search, recommender systems, and AWS for a global team with several engineers in the US.
  • Led the Agile and DevOps adoption for a US-based SaaS CRM startup to improve team performance and increase visibility. Investigated a cloud migration request, product analytics, and CDP options and wrote a concept paper on AI for the CRM.
  • Served as the technical Agile project manager and product manager for a US-based startup that built an innovative computer vision product with team members in three continents. Led the data labeling partner selection and managed the relationship.
  • Set up the team to deliver on weekly sprints, set up model accuracy measures and ground truth comparison procedures, wrote user stories, mapped business processes, set up the QA process and AWS administration, and tracked project issues and ideas.
  • Built a computer vision product for a global mobile app startup based in the UK. Recommended the approach, technology, and strategy. Coded and tested the model on AWS and set up measures for model accuracy. The success of this led to adoption.
  • Completed a POC for a startup in the UK that uses computer vision with medical images. The project goal was to democratize healthcare, and the successful completion of this POC enabled the founders to raise funds for scaling and a global solution.
  • Investigated the reasons for perceived long distribution cycle times for an FMCG client. Used data science techniques in R to suggest improvements, resulting in a potential improvement of 50% in cycle time while reducing operating costs.
  • Built a neural network model in R for predictive analytics on chaotic time-series data from industrial IoT sensors to reduce downtime and maintenance costs.
  • Took an active role in business development for this IoT solution while working at the data science and machine learning startup. Introduced Agile best practices to a 10-member team and got the team into a cadence of daily scrums.
  • Provided engineering, product management, and Agile coaching services for a company in South Africa. Performed a root cause analysis for a multi-year rewrite project and recommended a business-centric, Agile approach to projects.

CTO and Co-founder

2018 - 2019
Lima Payments
  • Streamlined IT infrastructure, processes, and resources to get the most value for the money spent.
  • Introduced Agile project management with a Kanban board on Trello and got the team into a rhythm of biweekly deployments.
  • Established best practices with respect to coding, code management, and deployments for our mobile and web application. The tech stack was Python, Android, and AWS.
  • Developed a detailed five-year budget forecast for IT resources, services, and infrastructure.
  • Played a key role in creating an investor pitch and represented the company to investors and accelerator programs.

Director/Division Manager, Information Technology

2007 - 2013
Rotary International
  • Spearheaded the Agile transformation of the organization along with the associated restructuring. This resulted in a significant increase in the number and size of enterprise projects delivered with much-improved client satisfaction.
  • Established an offshore captive development center in India in 2007 and successfully managed this relationship over the years. This resulted in a significant increase in the number of projects and support delivered within the same budget.
  • Managed 11 project managers as the interim PMO leader, promoted the concept of product ownership, led the creation and management of the project portfolio budget, and established a data-based project portfolio dashboard for the steering committee.
  • Increased the PMO's visibility and trust with the steering committee, which led to developing an IT strategic plan that dovetailed with the organization's strategic plan.

Enterprise Applications Division Manager | PeopleSoft Systems Division Manager | PeopleSoft Engineer

1999 - 2006
Rotary International
  • Oversaw an organizational restructuring that was supported by PeopleSoft systems.
  • Headed several large enterprise projects that were transformational in nature, such as the integration of the financial application with other custom and packaged applications.
  • Implemented, supported, customized, and performed upgrades on all the major PeopleSoft financial applications.

Computer Vision Project

Served as the technical agile project manager for a computer vision startup in stealth mode that has teams in three continents. Several pilot projects were completed and resulted in successful fundraising.

Worked with a global team of data scientists, infrastructure engineers, labeling companies, report writers, and researchers to build an innovative computer vision product. I was involved in all aspects of the project and wore multiple hats, including agile technical project manager, product manager, business analyst, data analyst, and QA engineer.

- Worked with the founder to document requirements, business processes, and go-to-market strategies, assisted by data-driven insights.
- Helped select and manage the relationship with labeling companies and the work they performed.
- Planned and implemented computer vision algorithms, training, and testing pipelines.
- Identified project issues and facilitated the team to brainstorm options to resolve them.
- Devised the calculation of accuracy metrics at various stages of the pipeline.
- Wrote the requirements for, managed, and tested an extensive rules-based algorithm to supplement computer vision.
- As the QA analyst, identified automation and outsourcing opportunities.
- Worked with a reporting company to produce complex custom reports.
- Managed the accounts, permissions, storage structure, and billing of AWS accounts.

Object Detection Using Computer Vision for Medical Images

Completed a POC to democratize healthcare using computer vision, a crucial step toward scaling and fundraising for a global solution.

My client wanted a POC to determine if computer vision using deep learning could identify medical problems from images. I used convolutional neural networks (deep learning) to deliver a successful POC for object detection on medical images with a small sample training dataset of 2,500 annotated images.

The tools used included Google Cloud Platform (GCP), Python, YOLO, and Jupyter Notebook. I set up Ubuntu VM on GCP to use GPU, loaded the necessary software, trained the model using cleansed data, and analyzed the results using object detection metrics. Then I ran another iteration with a larger training dataset and compared results to show improvement.

The client was pleased with the improvements shown and plans to obtain funding to scale the model to accommodate a larger training dataset. I submitted a comprehensive report and recommendations at the end of the POC. The report included an executive summary, approach, data cleansing procedure, GCP setup, training and testing procedure, and object detection metrics.

Computer Vision for Water Meter Images

Planned and executed a project using computer vision and deep learning to "read" water meter images and determine the reading with an accuracy of 85%.

- Read in over 36,000 images.
- Converted them into tensors.
- Matched them against readings from a CSV file and cleansed the data.
- Ensured that the images were of the correct data type and size.
- Shuffled image and reading data.
- Split into train and cross-validation (CV).
- Test loaded the InceptionV3 model.
- Used its weights on train, CV, and test data for transfer learning.
- Created separate hdf5 files with features, labels, and batch datasets for train, CV, and test batches.
- Trained on a shallow CNN model and transformed the output into the right dimensions for comparison.
- Plotted the loss and per-digit accuracy.
- Calculated the accuracy for training, CV, and test data.

I iterated the above process with multiple hyper-parameters and network sizes along with InceptionResNetV2 to improve the accuracy and used Agile Methodology to keep the project on track and provide visibility. The technologies used to work through this project included Floydhub Cloud Platform, Keras on TensorFlow, Python 3, Jupyter Notebook, and Excel.

Worldwide Loyalty Management Solution

Led the implementation of a loyalty management solution in seven countries to reduce the cycle time from several months to five days.

This project was implemented in seven countries simultaneously to replace a decades-old, mostly manual business process that had unpredictable cycle times and poor customer service with a simpler, consistent, and mostly automated business process that cut the cycle time to five business days.
1993 - 1995

MBA in Finance

University of Bombay - Mumbai, India

1988 - 1992

Bachelor's Degree in Engineering

University of Bombay - Mumbai, India


DevOps Culture and Mindset



Certified Scrum Master

Scrum Alliance


AWS Fundamentals: Going Cloud-Native



Certified Scrum Product Owner (CSPO)

Scrum Alliance


AWS Concepts



Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

Google Brain


Deep Learning Specialization



Coursera Mentor Community and Training Course



Machine Learning AtoZ



Machine Learning

Stanford University | via Coursera


R Programming

Johns Hopkins University | via Coursera


Getting and Cleaning Data

Johns Hopkins University | via Coursera


The Data Scientist’s Toolbox

Johns Hopkins University | via Coursera


Organization Change Management

Prosci, Chicago


DSDM Foundations Certificate - Agile Project Management & Development Methodology

DSDM Consortium, UK


Business Process Reengineering

Northwestern University, Chicago


Art of Leadership

Northwestern University, Chicago


MySQL Workbench, R, Jira, Microsoft Excel, Pandas, Trello, Google Colaboratory (Colab), AWS IAM, Confluence, Microsoft Project, Bitbucket, AWS CLI, PuTTY, Postman, Slack

Industry Expertise

Nonprofits, High-tech Startups


Agile, Scrum, Agile Project Management, DevOps, Business Continuity Planning (BCP), B2B, PRINCE2, Data Science, Kanban, B2C


Google Cloud Platform (GCP), Amazon Web Services (AWS), Jupyter Notebook


Scrum Master, Agile Coaching, Product Ownership, Certified Scrum Product Owner (CSPO), Certified ScrumMaster (CSM), IT, MySQL, Budgeting, Project Budget Management, Technical Program Management, Technical Project Management, Project Rescue, Project Scoping, Scope of Work, IT Recruitment, IT Project Management, Project Management, Consulting, New Product Development, Technical Leadership, Machine Learning, Information Technology, Convolutional Neural Networks (CNN), Deep Learning, DSDM, Agile Transformation, Business Process Re-engineering, IT Strategy, FloydHub, Business Development, Program Management, Amazon S3 (AWS S3), Fintech, PeopleSoft, Early-stage Startups, Data Analytics, Startups, Global Team Management, Computer Vision, Database Security, Google Cloud Machine Learning, System Requirements, Technical Analysis, Process Improvement, Business Continuity & Disaster Recovery (BCDR), AWS Cloud Computing Services, Artificial Intelligence (AI), Business Process Modeling, IT Program Management, Finance, Business Administration, Engineering, Systems Engineering, Proof of Concept (POC), Python 3, Loyalty Programs, Business Process Automation, Business Processes, Budget Management, Quality Improvement, Labeling, Data Quality, Business Analysis, Data Analysis, Keras, TensorFlow, Python, Google Maps API, Oracle 11g, Mobile Apps, FileZilla, CTO, SaaS, Product Analytics, Natural Language Processing (NLP), Product Management, Cybersecurity, Generative Pre-trained Transformers (GPT)

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