You will get talented team of ML Engg having production experience of ML & GenAI apps
Project details
We are a startup founded by a team that has collaborated since 2010. With over a decade of experience in Big Data, Machine Learning, and AI (including Generative AI), our founders have honed exceptional skills in these technologies.
We pride ourselves on maintaining a small, highly focused team that consistently delivers client projects faster than our competitors. The quality of our code is a key differentiator, leading to reduced rework and significant cost savings in infrastructure for our clients.
Our engineers work under the direct supervision of the founders, ensuring unwavering attention to quality. Over the past 12 months, we have made significant advancements in Generative AI and MLOps, building on our strong foundation in traditional machine learning models and Big Data solutions.
The Timeline of 70days is selected as the max value as we dont know the size of the projects
We pride ourselves on maintaining a small, highly focused team that consistently delivers client projects faster than our competitors. The quality of our code is a key differentiator, leading to reduced rework and significant cost savings in infrastructure for our clients.
Our engineers work under the direct supervision of the founders, ensuring unwavering attention to quality. Over the past 12 months, we have made significant advancements in Generative AI and MLOps, building on our strong foundation in traditional machine learning models and Big Data solutions.
The Timeline of 70days is selected as the max value as we dont know the size of the projects
Machine Learning Tools
Amazon SageMaker, Apache Spark, Apache Spark MLlib, Azure Machine Learning, ChatGPT, Cloudera, Databricks Platform, Databricks MLflow, Google AutoML, GPT-3, Hortonworks, Keras, Microsoft Excel, MLflow, NumPy, pandas, Python, PyTorch, SQL, TensorFlow, Tesseract OCR, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$17
|
Standard
$30
|
Advanced
$50
|
|---|---|---|---|
| Delivery Time | 70 days | 70 days | 70 days |
Number of Revisions | 0 | 0 | 0 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | |||
Source Code |
Frequently asked questions
About Div
Project / Program Manager
Pune, India - 8:10 pm local time
Throughout my career, I have experience in leading and growing various units of a business like
» Company Strategy
» People Management
» Client Engagements & Business Development
» Project Deliveries
» Operations
I specialize in scaling Tech Teams.
Some of the major clients I have worked with include Availity, KOHLS, Albertsons, GfK, Netcracker, Qoredo ( previously QTel), Morgan Stanley, Adidas, etc.
MAJOR ACHIEVEMENTS:
• Successful Exits from companies in Bigdata & ML domain
• Built and grew agile Scrum teams from 0 to 80 employees in only 3 years
• Co founded a company where we build E2E product from concept to launch in 18 months
• Completed the Wharton Business Strategy: Competitive Advantage course.
A firm believer in humanity and nature, when I am not busy doing something amazing at work, I can be found traveling and meeting awesome people across the globe.
Skills:
Leadership:
Strategy, Executive Management & Operations, Leadership Development, Business Development, Negotiations.
Product / Project :
Product Management, Stakeholder Management, Software Business Plan & Strategy, Vendor Management
Technology:
Big Data (Hadoop, HDFS, Spark), GenAI, Machine Learning, Java, Technology, Cloud technologies (AWS, GCP, Azure),
Steps for completing your project
After purchasing the project, send requirements so Div can start the project.
Delivery time starts when Div receives requirements from you.
Div works on your project following the steps below.
Revisions may occur after the delivery date.
Understand the Requirement
We engage in discussion / calls to understand the requirements and document them in a tool (if its not already done)
Pick up stories & Develop
Work with the team to prioritize stories and start developing them in local environment. Check the explanability & Interpretability of the Models.