# Dhanush Patel > Senior Software Engineer - AI/ML/Agents/Data Location: San Francisco Bay Area, United States Profile: https://flows.cv/dhanush Software Engineer with 5+ years experience specializing in building and deploying data and machine learning pipelines with the ability to cross-functionally work from creating MVPs to scaling existing services in startup and large company environments. Currently Software Engineer at Covariant.ai on the AI Infrastructure developing data pipelines and cloud services spanning robot stations to cloud to support computer vision and machine learning models on industrial robots. Previously Software Engineer at Salesforce improving search relevance through machine learning and natural language processing infrastructure and algorithms. Core skills: Python, Java, JavaScript, Kubernetes, AWS, ML Full skills: Python, Django, pytest/mypy/black, Kubernetes, Docker/Docker Compose, SaltStack, PostgreSQL, Terraform, AWS (EKS, ECR, RDS, SQS, SNS, S3, Lambda), Datadog (metrics monitoring), Github Actions (CI), Bazel (build system), gRPC/protocol buffers, HTTP, Airflow, Java, Spring Boot, Maven, Node.js, Flask, Express, Pandas, Matplotlib, JUnit, Mockito, React, Redux, Spring, Jest, Enzyme, PyTorch, TensorFlow, scikit-learn, Ray, SkyPilot Technical domains: Software Engineer, ML Engineer, Data Engineer, Data Science Non-technical domains: leadership, entrepreneurship Certifications: Certified Kubernetes Application Developer (CKAD) – CNCF, TensorFlow Developer – Google Fun fact: I've been to 45+ hackathons and won 25+ prizes! Here are some useful links: (for best resume viewing experience: print (top right corner) > save to pdf) Resume: https://1drv.ms/w/s!AkxclidsqQNamT9zKLX9_auC4DLh Github: https://github.com/Dhanush123 Outdated links: Devpost: http://devpost.com/DhanushP Kaggle: https://www.kaggle.com/dhanushp Medium: https://medium.com/@dhanush.patel Play Store: https://play.google.com/store/apps/developer?id=Dhanush+Patel ** Hackster: https://www.hackster.io/Dhanush123 * Alexa: https://www.amazon.com/s/ref=nb_sb_noss?url=search-alias%3Dalexa-skills&field-keywords=octabytes ** *many Devpost wins haven't been marked, 1 Hackster win hasn't been marked, and a few wins are on HackerEarth but that site doesn't list wins on a user profile **not all apps/skills published are still up as of April 2019 ## Work Experience ### Senior Software Engineer - AI Cloud / Agentforce @ Salesforce Jan 2023 – Present | San Francisco Bay Area ### Software Engineer - AI Infrastructure @ Covariant Jan 2022 – Jan 2023 | San Francisco Bay Area - Launched and improved data pipelines for generating video, scanner, telemetry, and metadata files from 100s+ robot stations, uploading 100s TB+ to S3, processing into Robot Data Platform (RDP) via SQS, Kubernetes, Python services on AWS + Terraform - Built RDP with Django, PostgreSQL (RDS) on AWS (EKS), handling 1000+ requests/sec peak for AI researchers, robot app developers, and deployment engineers to access, filter, and modify data via web UIs and Python client - Designed annotation pipelines using RDP, S3, SQS, Lambda functions to send images and videos to vendors so the enriched data can be used for machine learning model training and robot performance metrics - Full list of tech used: Python, Django, pytest/mypy/black, Kubernetes, docker/docker compose, SaltStack, PostgreSQL, Terraform, AWS (EKS, ECR, RDS, SQS, SNS, S3), Datadog (metrics monitoring), Github Actions (CI), Bazel (build system), gRPC/protocol buffers, HTTP, PyTorch, Ray, SkyPilot ### Software Engineer - Conversational Search Relevance @ Salesforce Jan 2021 – Jan 2022 | San Francisco Bay Area - Migrated on-prem Scala Spark jobs, processing triple-digit TBs of app interaction logs daily, with Airflow to AWS EKS (Kubernetes) + S3 with Spinnaker and Java orchestration libraries - Turned the Natural Language Search (NLS) metadata system into a platform to enable self-service NLS support for Salesforce entities with Java and Spring Boot, thus increasing the number of supported entities by 20% in its 1st quarter - Increased number of supported search queries by 20% by implementing NLP tagging algorithms in Java - Enabled users to do query remediation by improving NLP inference logic in Java for a TensorFlow Named Entity Recognition (NER) model to generate multiple interpretations and doing data analysis with Python/Pandas/Matplotlib to select optimal parameters - Used Splunk/Kibana for logs analysis, Grafana for metrics monitoring, and Protocol Buffers (protobufs) for inter-systems communication ### Software Engineer - Service Admin Experience @ Salesforce Jan 2020 – Jan 2021 | San Francisco Bay Area - Launched new Service Setup Assistant product to reduce Time to Value (TTV) from 8 months to 2 weeks and setup clicks by 90% - Wrote backend code with Java, Spring, JUnit, Mockito and frontend code with JavaScript - Used Splunk for logs analysis ### Software Engineer Intern @ Salesforce Jan 2019 – Jan 2019 | San Francisco Bay Area · Built infrastructure for a new deep learning Learning To Rank model involving feature extraction and preprocessing, metadata loading, and model serving across a microservices platform and monolithic repo using Java and Protocol Buffers · Created the Keras/TensorFlow equivalent of a Data Scientist’s PyTorch model and integrated it into the infrastructure · Worked across 5 code repos and 3 runtime services, worked with an Architect and Data Scientist, and produced results that convinced the Search Relevance team to A/B test my work · Learned to work with and debug in multiple codebases, communicate and collaborate closely with others (specifically an Architect and Data Scientist) to meet a common goal, and pick up new technologies independently --- · Added distributed tracing throughout 2 Search Cloud endpoints with Apache Zipkin, Docker, Java and tested with JUnit ### Machine Learning Engineer Intern @ Workep Inc. Jan 2019 – Jan 2019 | San Francisco Bay Area · Cleaned/augmented/tokenized/embedded data and created text classification multiclass and multilabel SVM/MLP/CNN/LSTM models to suggest priority/content/user tags for to-do tasks with Pandas, NLTK, TensorFlow, Keras, scikit-learn, imbalanced-learn · Organized notebook code and models into a Flask server and Google Cloud Storage bucket, then deployed the server with Docker · Learned to work in a fast-paced environment and prioritize work since Workep was a 20 person seed stage startup going through the Berkeley SkyDeck accelerator program and I was the only person with SWE experience on the 4 person ML team during my time working there ### Software Engineer Intern @ Salesforce Jan 2018 – Jan 2018 | San Francisco Bay Area · Created a web app from scratch to make creating, deploying, and monitoring machine learning models easier and error-free at scale for Data Scientists by removing the need to use a CLI · Got UI, UX, and features buy-in from stakeholders by presenting Adobe XD prototypes, created the app with React/Redux/Spring, tested it with Jest/Enzyme/JUnit, and presented final product to Search Cloud after which Data Scientists started using it ## Education ### Bachelor's degree in Data Science University of California, Berkeley ### Minor in Computer Science University of California, Berkeley ### Associate’s Degree in Computer Science Diablo Valley College ### High School California High School (San Ramon CA.) ## Contact & Social - LinkedIn: https://linkedin.com/in/dhanushp --- Source: https://flows.cv/dhanush JSON Resume: https://flows.cv/dhanush/resume.json Last updated: 2026-03-29