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Vetted Data Ingestion Professionals
Pre-screened and vetted.
Gowtham Alasakani
Junior Full-Stack Software Engineer specializing in AI and data pipelines
“Built and shipped a production AI assistant for a web-based loan/interest calculator that helped users understand EMI results and optimize inputs. Demonstrated full-stack ownership across responsive UI, Node.js APIs, and LLM integration, with a strong focus on prompt refinement, guardrails, caching, fallbacks, and post-launch iteration driven by logs and user behavior.”
Ekta Mulkalwar
Junior Machine Learning & Full-Stack Engineer specializing in applied AI systems
“Master’s thesis focused on building and deploying a gait-based biometric authentication system using mobile accelerometer time-series data as an alternative to passwords/2FA. Emphasized real-world robustness by addressing sensor noise and variability (phone placement, walking speed, footwear) and improving safety using biometric metrics like FAR/FRR and EER, while collaborating closely with a non-ML thesis advisor.”
Farrah Ellis
Senior Software Engineer specializing in backend systems, cloud, and AI applications
“Engineer with growth-stage startup experience on a 6-7 person cross-functional team, working across backend, data, and frontend systems. They’ve driven concrete improvements to high-volume data ingestion pipelines through batch processing and database optimization, and have built B2B SaaS data platforms for enterprise customers with multi-tenant support, integrations, and scalable backend services in Python and Go.”
Mid-level Full-Stack Engineer specializing in healthcare, mobile apps, and AI
Junior Backend Software Engineer specializing in APIs, databases, and AI applications
Mid-Level Software Engineer specializing in FinTech data pipelines and backend APIs
Mid-level Full-Stack Engineer specializing in backend systems and automation
Entry-Level Machine Learning Researcher specializing in HPC telemetry modeling
Junior Full-Stack Developer specializing in JavaScript, React, and MongoDB
Entry-level Machine Learning Engineer specializing in LLMs, RAG, and data pipelines
Mid-level Full-Stack AI Engineer specializing in web and generative AI solutions
Mid-level Software Engineer specializing in Python automation and GenAI on AWS
Mid-level Data Engineer specializing in cloud-native batch and streaming pipelines
Mid-level Applied AI Engineer specializing in LLM systems for EdTech and FinTech
kireeti Sangarsh
Mid-level Data Engineer specializing in cloud ELT pipelines and analytics engineering
“Data engineer who has owned end-to-end ELT pipelines on Airflow + AWS (S3/Glue/Lambda) with Snowflake/Redshift, processing millions of records per day and tens of GBs via PySpark. Built strong data quality and reliability practices (40% quality improvement, 99%+ uptime), and also designed a resilient web-scraping system with anti-bot defenses and schema-change versioning plus REST APIs for serving curated data.”
Bhuvan Bethapudi
Entry-level Software Engineer specializing in backend and full-stack systems
“Built production-style backend and AI systems across internship and project work, including a real-time sports platform backend and a Smart Email Assistant using GPT-4. Stands out for combining classic backend performance engineering with practical LLM workflow design, including measurable latency improvements, high uptime, and debugging of non-deterministic model behavior.”
Vedant Kankate
Entry-level Full-Stack Software Engineer specializing in web and data systems
“Full-stack engineer with strong TypeScript/Firebase and MongoDB depth who has built research and student-scale systems end-to-end, including GCP data pipelines and Dockerized microservices. Particularly interesting for stepping beyond a frontend remit to build NLP models with NLTK that are actively used in an academic research project's Phase 2, showing initiative and real downstream impact.”