Vetted Algorithms Professionals

“Machine learning/NLP engineer who built a production-oriented retrieval-based AI system at Morgan Stanley for healthcare use cases, combining RAG over unstructured patient records with deep-learning medical image segmentation (U-Net/Mask R-CNN). Strong in end-to-end pipelines and MLOps (Spark/MongoDB, AWS SageMaker, CI/CD, monitoring, automated retraining) and in entity resolution/data quality validation for noisy clinical data.”

Allan Farinas

Screened

Senior Full-Stack Software Engineer specializing in Python and AWS

West Covina, CA11y exp

“Backend/data engineer who has built production Python microservices (FastAPI) and AWS-native platforms for event ingestion and analytics, combining ECS/Fargate + Lambda with CloudFormation-driven environments and strong secrets/IAM practices. Experienced modernizing legacy logic with parallel-run parity validation and safe phased cutovers, and has demonstrated measurable SQL tuning wins (20–30s down to 1–2s) plus incident ownership in Glue/Step Functions ETL pipelines.”

Natalie Tsang

Screened

Intern Mechatronics/Robotics Software Engineer specializing in ADAS and ROS2

Waterloo, ON1y exp

“Robotics software engineer with experience spanning embedded C++ control on microcontrollers and ROS/ROS2 production systems in automotive and marine robotics contexts (Harbinger Motors, Impossible Metals). Has deep hands-on experience debugging real-time image pipelines (DDS/QoS tuning, HIL stress testing) and building large automated test suites (1200+ tests) plus CI/CD (Dockerized Playwright tests on Jenkins).”

“Game developer with experience on DreamCraft and KartRider Rush+, focused on Unity/C# gameplay systems, AI behavior, and multiplayer synchronization. Stands out for building a modular character customization system shared across teams and for tuning AI karts to feel more human while supporting different player skill levels.”

Anirban Ghosh

Screened

Mid-level Machine Learning Engineer specializing in data science and cloud systems

Seattle, WA4y exp

“ML engineer who independently pitched and built a recommendation engine at Danske Bank in a legacy fintech environment, creating compliant data pipelines and deployment infrastructure from scratch and delivering a 62% engagement lift with 70%+ advisor adoption. Also worked at AWS on classification and GenAI-powered reporting systems, with strengths spanning production ML, platform setup, monitoring, and research-to-production optimization.”

“ML/AI engineer focused on production NLP and voice AI systems in the restaurant tech space, with hands-on work spanning ASR, intent classification, LLM fine-tuning, and deployment monitoring at Presto AI. They highlight a 15% improvement in full-AI ordering rate and also built a restaurant sentiment analysis product at Wisely that they say became a standout feature in a $10M acquisition context.”

“ML/LLM systems engineer who has owned AI support automation products end-to-end, including ServiceNow-integrated incident routing, RAG-based resolution suggestion systems, and production stabilization. Stands out for combining hands-on platform work across PySpark, AWS Glue, FastAPI, Kubernetes, and Pinecone with measurable operational impact, including 30-35% MTTR reduction and 25-30% improvement in first-touch resolution.”

“Backend/ML-focused engineer with experience spanning fintech, sales enablement, and medtech, including a Capital One capstone and a Singapore medtech startup internship. Stands out for owning end-to-end AI/backend systems, from a GenAI sales pitch platform that cut prep time by 50% to an ultrasound-guidance MVP for non-expert operators in a highly ambiguous domain.”

“Upcoming IIT KGP graduate with production-level frontend experience at Tryp.com, where they co-owned a sophisticated browser-based travel booking interface for global users. Stands out for combining React/TypeScript product work with unusually strong browser rendering and performance optimization skills, plus evidence of measurable UX and load-time improvements.”

Gaurav Sherwani

Screened

Mid-level product and data engineer specializing in FinTech and AI

Washington, DC5y exp

“Data engineer and technical product manager with a strong pre-sales-style background in highly regulated financial environments, translating complex data infrastructure work into business cases, compliance signoffs, and leadership buy-in. At UBS, they drove a cloud migration with $2M savings and built regulatory automation that beat benchmarks, while at Omnic.ai they worked directly with users on a GPT-4 feature that doubled MAU and lifted subscriptions 20%.”

“Backend engineer with hands-on experience scaling a Python/Flask incident-logging platform processing thousands of daily logs. Strong in performance tuning (PostgreSQL/SQLAlchemy query optimization, partitioning, summary tables) and reliability patterns (Redis caching, Celery background workers, Docker + Jenkins CI/CD), with some multi-tenant data isolation experience via separate DBs/schemas.”

“AI engineer with robotics perception experience at Forterra, building and deploying moving-object/obstacle detection models into real-time robot pipelines. Addressed training crashes/latency via sub-batch training and optimizer tuning, and improved debugging using ROS/ROS2 tooling with 3D voxel visualization and color-coded validation.”

Daniel Panrong Dai

Screened

Junior Software Engineer specializing in AI and full-stack development

New York, NY1y exp

“Consulting-background AI practitioner who led a production LLM pipeline on Snowflake Cortex to map hundreds of thousands of messy OCR/form-based contract fields into standardized Salesforce fields, including confidence scoring and an LLM-driven feedback loop. Strong focus on real-world constraints—token limits, cost control, and evaluation without ground truth—paired with frequent stakeholder-facing progress reporting.”

Jeff Cushler

Screened

Executive Technology & Product Leader specializing in Healthcare IT, SaaS, and Cloud Transformation

Austin, TX30y exp

“Startup product/enterprise-stack builder who helped take Ventric Health from R&D to a market-launched healthcare product in 2024, operating in a $34M-raised, revenue-generating model leveraging Medicare C reimbursement through providers. Previously drove adoption of an integrated K-12 digital learning platform distributed to 100+ institutions over two years, with reported improvements in test scores.”

Aditya Jhaveri

Screened

Mid-level Software Engineer specializing in AI, big data, and distributed systems

Jersey City, NJ3y exp

“Software Developer at NYU (GEMSS) focused on scaling and optimizing a data-heavy asset management web app, including migrating/optimizing data access via Google Sheets API and Firestore. Previously an SDE at Sainapse working on Spring Boot microservices POCs (Kafka, Hadoop at 2B+ record scale). Built an end-to-end Apple Wallet coupon generation/redemption system using PassKit + Google Apps Script with measurable ops impact (40% efficiency gain).”

“Built and stabilized production data pipelines in clinical genomics, including integrating a qPCR step into Baylor Genetics' workflow with a focus on reliability, turnaround time, and reducing manual intervention. Also has hands-on LLM production experience, creating a Python/OpenAI-based translation evaluation pipeline that reduced manual review time by 70% and improved scoring consistency.”

“Full-stack engineer with strong enterprise delivery experience across manufacturing and semiconductor use cases, owning deployments from discovery through post-launch support. Stands out for combining traditional product engineering with applied GenAI workflows and data pipeline reliability work, including a manufacturing app that reportedly saved a Fortune 500 customer about $6M and an AI chat panel adopted by 70% of pricing analysts.”

Akhila Gadige

Screened

Mid-level Full-Stack Developer specializing in Python, Java, cloud, and GenAI

Remote4y exp

“Backend-leaning full-stack engineer who has built and operated high-throughput GPU telemetry and task/event platforms using React, FastAPI, PostgreSQL, Redis, Celery, and Kubernetes. Stands out for hands-on ownership of production performance at scale, including partitioning 100M+ row tables, fixing timeout bottlenecks, and delivering measurable gains like 3x throughput and 95% fewer timeout errors.”

“Full-stack engineer who built an LLM-powered productivity web app (LifeOS) end-to-end with TypeScript/Next.js, Prisma, and Postgres, emphasizing fast iteration with stable API contracts and an isolated AI service boundary. Also built a security/compliance login-verification workflow at Medpace used within an internal admin portal for thousands of employees, and has AWS experience orchestrating batch GPU workloads with robust retry/idempotency patterns.”

“Software developer with healthcare operations experience at Epic Systems (Referrals & Authorizations), delivering customer-facing tooling to speed manual insurance authorization/denial documentation and support future automation. Also supported an HRIS migration to Workday at Aloe Yoga, solving legacy ID interoperability via scripting and mapping, and demonstrates strong production debugging and test-driven maintainability practices.”

“Full-stack engineer with production experience building a security integrations portal in Next.js (App Router + TypeScript), using server components and typed route handlers as a secure proxy to multiple third-party security vendors. Demonstrated ability to scale performance significantly (server-side re-architecture for 1M+ datapoint dashboard filtering; Postgres query tuning from 1–2s to <200ms) and to own features post-launch (reliability, caching/background sync, and rapid onboarding of new integrations) in a pre-Series B through post-Series C environment.”

Jackson Dike

Screened

Entry-Level Software Engineer specializing in Machine Learning and AI

Remote1y exp

“Master’s-level candidate with an academic project portfolio, including ownership of a Python-based video game recommendation system using unsupervised clustering. Has hands-on experience designing the system approach and validating recommendation quality with test cases, plus teaching assistant experience instructing Git/GitHub workflows; limited exposure to Kubernetes, GitOps, and large-scale infrastructure.”

Daniel Wahab

Screened

Junior Embedded/Robotics Software Engineer specializing in autonomous drones

Ithaca, NY2y exp

“Robotics software engineer focused on simulation-heavy development, recently building a 6-robot swarm in Gazebo with custom terrain and per-robot A* path planning while researching PSO-based swarm algorithms. Experienced with ROS 2 multi-node communication patterns and autonomous drone simulation using ArduPilot (ap_dds), with a track record of debugging real-time behavior issues through disciplined isolation and incremental testing.”

“Early-career builder with hands-on project experience spanning Python data processing, a Chrome extension for autofilling job applications, and a sign-language glove system integrating sensors, microcontrollers, and a web interface. Stands out for approaching student and project work with a production-minded focus on validation, modularity, edge cases, and reliability.”