You will get machine learning model deployment on Azure, AWS or GCP cloud.
Rising Talent
Project details
• We are a team of 5 experienced Data Scientist/ML engineers with certifications on Azure and Amazon clouds and 15-20 years spent in scientific research.
• As a project outcome, you will get a working code, deployed model and instructions on how to use and support it. With many years of experience in freelance and consulting agency environments, we care deeply about our clients.
• Answer your questions daily, available even after the project is finished.
• Prices shown are approximate and may vary based on project volume and needs.
• As a project outcome, you will get a working code, deployed model and instructions on how to use and support it. With many years of experience in freelance and consulting agency environments, we care deeply about our clients.
• Answer your questions daily, available even after the project is finished.
• Prices shown are approximate and may vary based on project volume and needs.
Machine Learning Tools
Amazon SageMaker, Apache Spark, Apache Spark MLlib, Azure Machine Learning, ChatGPT, Cloudera, Google AutoML, H2O, Kubeflow, MLflow, NumPy, Open Neural Network Exchange, pandas, Python, PyTorch, QlikView, R, scikit-learn, SciPy, SQL, Tableau, TensorFlow, Vertex AI, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$300
|
Standard
$2,000
|
Advanced
$5,000
|
|---|---|---|---|
| Delivery Time | 3 days | 10 days | 30 days |
Number of Revisions | 1 | 2 | 2 |
Number of Scenarios | 3 | 3 | 3 |
Model Validation/Testing | - | ||
Model Documentation | |||
Data Source Connectivity | - | ||
Source Code | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$150 - $1,000
Data Source Connectivity
(+ 3 Days)
+$300
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AC
Angel C.
Sep 25, 2025
60 minute consultation
Dmitry was exceptional. A true professional in the DS field. I came away a lot smarter from our conversation.
CC
Charles Jan C.
Sep 24, 2025
Seeking Procurement and Innovation Leads in Electric Utilities - paid survey
JS
Jai S.
Jan 6, 2025
Create Local Tool to Perform Multi Objective Optimization using AI
Amazing work! Dmitry was able to quickly understand the complex details of my project and deliver a high-level end product.
About Dmitry
Data Scientist/ML Engineer, AI, Big Data, PhD in Particle Physics
100%
Job Success
Plainfield, United States - 11:58 pm local time
Big data and analytics enthusiast, permanent learner, with about 18 years experience of data analysis and research in experimental particle physics and 10 years of data science experience in industrial settings (advertising, automotive, supply chain, energy&utility and consulting).
Co-author of many software packages in experimental particle physics and industry.
Leader of a few algorithmic and physics research groups and data science groups in industry.
Supervised many undergraduate/PhD students, data scientists and interns in various projects.
Delivery of end-to-end ML services in business companies using on-premise and cloud technologies.
Primary author of more than 30 papers published in major peer-reviewed physics journals
with application of machine learning algorithms in physics experiments and industrial environments: inspirehep.net/author/profile/D.V.Bandurin.1
Business website: solveum.ai
A few projects have been either delivered or in progress on Upwork.
Skills:
– Programming in Python, R, C++, Scala, Fortran, MatLab
– SQL (incl. Postgres, Redshift, Snowflake), noSQL (Mongo, Redis, BigQuery, Cassandra, Neo4j, ElasticSearch);
– Big data processing using Hadoop, Databricks, Spark, Hive, Impala;
– Machine learning using scikit-learn, MLLib, MLFlow, TensorFlow, Keras, PyTorch;
– Distributed deep learning using Dask, Ray, Horovod;
– Reinforcement learning using RLLib, Ray, COACH, OpenAI Gym;
– Natural language processing [incl. Gensim/NLTK/SpaCy; GloVe/Word2Vec/FastText/BERT, etc];
– Computer vision [incl. OpenCV, OCR];
– Azure Cloud (Databricks, Delta Lake, Azure ML, Synapse Analytics, Azure IoT Hub, IoT Edge, Functions);
– AWS Cloud (RDS, Amazon S3, EC2&ECR, Elastic Beanstalk, Lambda, SageMaker, etc);
– Google Cloud (Vertex AI, BigQuery, DataStudio, Kubeflow, AutoML);
– IBM Watson (Audio and Text modeling, transcription services);
– Data visualization (Tableau, Power BI, QuickSight, Python&R libraries, e.g. Plotly, Dash, Shiny);
Recommendations: see dmitrybandurin/details/recommendations/ at LinkedIn.
Steps for completing your project
After purchasing the project, send requirements so Dmitry can start the project.
Delivery time starts when Dmitry receives requirements from you.
Dmitry works on your project following the steps below.
Revisions may occur after the delivery date.
Project goals.
Client composes a document that describes a problem, goals, and acceptance criteria for each step and overall.
Proposal approval
Client receives and approves proposal with follow-up steps.